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Friday, October 30, 2015

Do social media likes & followers = popularity?

Friday, October 30, 2015

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Do social media likes & followers equal popularity?

Sunny Stuart Winter graduating from Bucks New Uni
After graduating from my BA (Hons) Music Management & Artist Development last month, and with ample requests to read my dissertation on social media use by bands and artists, I felt like it was time to upload this for you the reader, to share my findings from the best part of 7 months, late night library visits and 9,386 words.

Specialising in social media and social influence, this research was such a joy to work on. I am currently looking for opportunities to publish this in academic journals for peers to build upon for further research.

Although very in depth, somewhat heavy perhaps, I would love to know your thoughts and conclusions of what you are about to read. A lot of time went into this, i'm proud to have received a First for it and I look forward to discussing with you all on social media (Twitter: @sunnynorwich).

To cite this dissertation, please use the following reference:

Winter, S. (2015). Are social media ‘likes’ and ‘‘followers’’ a true representation of an artist’s popularity?. Available: www.sunnystuartwinter.com - Last accessed TODAY'S DATE.

Are social media ‘likes’ and ‘followers’ a true representation of an artist’s popularity?

What influences Facebook & Twitter users to ‘like’ or ‘follow’ bands & artists online?


This research aims to understand what influences Facebook and Twitter users to ‘like’ or ‘follow’ bands and artists on social media. It centres on the behaviour and psychology of group norms and social proof to investigate social media metrics as an indication of popularity. With social media still in its early stages and constantly developing, this research is crucial in understanding user behaviour in connecting with bands and artists online, allowing those within the Music Industry to understand how the behaviour of social group peers and high numbers of ‘likes’ or ‘‘followers’’ can influence other Facebook or Twitter users to ‘like’ or ‘follow’ bands and artists. It is also vital to researchers and practitioners in the study of influence theory with regards to new technologies, such as social media.

This study was completed using an online survey comprising of quantitative research by way of Likert-type questions with a 7-point Likert Scale to rate participant’s level of agreement or disagreement to a range of statements. The survey was shared on both Facebook and Twitter to a purposive sample to represent the behaviour of social media users.

The key findings of the study concluded that social media users consider the number of Facebook page ‘likes’ or Twitter ‘‘followers’’ a band or artist has indicates their level of popularity but that these numerical metrics alone do not influence users to ‘like’ or ‘follow’ a band or artist.


This research hopes to address the question, “Are social media ‘likes’ and ‘‘followers’’ a true representation of an artist’s popularity?” To further discuss this subject, additional questions must be asked to understand the reasons why people ‘follow’ or ‘like’ a particular artist on social media, whether the majority of people only subscribe to their favourite artists or whether there are other influences, such as subscribing to artists because they are deemed cool or because their friends like them. What, if anything, do ‘‘followers’’ and ‘likes’ mean with regards to placing a societal value on popularity to peers?

Social Media networks can be traced back to 1999 where Friends Reunited rose to prominence, however it was not until the first dominant social network, MySpace; following in 2003, where music artist profiles could be created to gain fans and build a fan-base online. This was the first instance where people would gauge an artist’s popularity by the amount of fans they had ‘following’ them and equally, fans could be influenced to ‘follow’ similar artists that were popular or that their friends ‘followed’ online.

This followed with the introduction of Facebook in 2004, the social network that saw the creation of company or fan pages in 2007 and which surpassed MySpace as the most popular social network by way of total number of monthly unique visitors in 2008 (UNCP, 2013). Twitter, meanwhile, launched in 2006. Currently, Facebook has over a billion users (Lunden, 2014) and Twitter has 271 million users (Apuzzo, 2014). Most artist profiles on Twitter and Facebook seek to have high numbers of ‘followers’ to appear popular and many fans seem to connect with large amounts of artists across each social platform, but their intentions for this are unclear. 52% of the teenage Facebook users of the iGeneration, those born in the 1990s, clicked ‘like’ daily or even several times a day (Rosen, 2012).

Social media is now one of the most important marketing tools, giving people the power to see what they want depending on who they ‘follow’ or ‘like’, to communicate with fellow fans and giving them a direct voice to their favourite bands and artists. This has seen a rise in sponsored posts on both Facebook and Twitter where artists pay for their content to be boosted to gain the attention of social media users who are as yet connected to that band or artist. This technique focuses on targeting an exact audience, a target market of potential fans, to elevate the artist into being noticed by them.

Metrics of ‘likes’ and ‘followers’ tend to give an impression of how well known a band or artist is and this research will look into what high figures of ‘likes’ or ‘‘followers’’ means to social media users, whether it influences them to also ‘like’ or ‘follow’, or whether it has little to no affect at all. 

Presently, many bands and artists are aiming to get high numbers of ‘likes’ and ‘‘followers’’ without maintaining the interaction between themselves and their fans. It is often considered that purely having a large number of ‘likes’ and ‘‘followers’’ will lead to assumptions by non-fans that a band or artist is popular but there are now many ways to forge profiles and manipulate figures, so how many ‘likes’ and ‘‘followers’’ must a band or artist have to be deemed truly popular? This research hopes to investigate whether high numbers of ‘likes’ and ‘‘followers’’ actually means anything to Facebook and Twitter users, as well as understanding what aspect of ‘like’ and ‘follower’ metrics are social media users influenced by, whether influenced by the number of likes and ‘followers’ alone, influenced by their close friends on or offline, or whether more specific traits provide more influence.

This research is worth investigating because social media is a key part of promotion and marketing for those within the Music Industry, bands and artists alike, as well as being a significant platform for direct interaction between themselves and their fans. For the business side of the Music Industry, this often means the communication of products, such as new album releases or merchandise. Understanding how bands and artists can influence non-fans to ‘like’ or ‘follow’ them, as well as influencing fans to spread word of mouth to their peers would uncover valuable insight into how best to promote an act to stand out above the millions of other bands and artists on both Facebook and Twitter.

The most popular mainstream artists often have millions of users connected to their Facebook and Twitter accounts. Taylor Swift has 70 million Facebook profile likes and over 56 million Twitter ‘followers’. Ed Sheeran has over 11 million Facebook profile likes and over 13 million Twitter ‘followers’. In comparison, Don Broco, a lesser-known band that has still obtained some mainstream success have 69 thousand Facebook profile likes and 47 thousand Twitter ‘followers’.

Compare these with an upcoming, unsigned band like Morain who have 4.5 thousand Facebook page likes and just 2.5 thousand Twitter ‘followers’ and it shows a ranking of perceived recognition, but do these metrics give an honest representation of popularity? Furthermore, how would these social media metrics influence users to ‘like’ or ‘follow’ bands or artists and what other factors offer influence?

With social media still in its relatively early days, the influence it exerts has little to no documented research in comparison to social theory in the offline world so this research hopes to bridge a gap in knowledge to then be built on as social media continues to develop.

Influence as a broad concept will be discussed, with elements of social proof, how people look to similar others for an example of how best to behave, and group norms, behavioural traits within social groups, scrutinized with regards to their impact on social media users behaviour. Ultimately, this research will take the past explorations of social influence and apply them to the social media environment on Facebook and Twitter.

This research will be undertaken using quantitative data by way of an online survey distributed via both Facebook status and Twitter tweet. This is an effective way to gain data as it gives an equal opportunity for a wide range of participants to partake in the research to make sure that it is fair. Likert-type questions and Likert scales will be used to give a range of seven options to measure the participant’s agreement or disagreement to a number of statements resulting in data which will capture social media users beliefs regarding social media likes and ‘followers’, and the influence it exerts.

Literature Review


As a definition, influence can be described as the capacity to have an effect on the character, development or behaviour of someone or something (Oxford English Dictionary, 1989), it is a type of psychological force” (Cartwright, 1959). Kiecker and Cowles (2002) have researched this area and discuss five different forms of word of mouth influence which include opinion leaders, market mavens, purchase pals, innovators and early adopters, and surrogate consumers. 

Whilst Solomon (1960) has previously addressed many forms of influence such as interpersonal trust, cognitive balance and interpersonal power, which built upon research by Deutsch (1957) regarding the influence of co-operative, individualistic and competitive motivational orientations, my focus for this research is on interpersonal influence and in particular, word of mouth.

Influence as a vast concept has been described to have multiple levels. These include the physical aspect of the influence process described by Nowak and Vallacher (1998), the psychological level discussed by Cialdini which are described as some general mechanisms of influence that tend to be more or less universal for human beings (Wosinska et al, 2000, p.128) and the culturally specific level; mechanisms of influence that are distinctive to a given cultural context (Wosinska et al, 2000, p.128).

The birth of the Internet altered influence theory, unrestricting interpersonal communication from a small circle of family and friends as personal sources, where source credibility was quite obvious and rarely suspect (Kiecker and Cowles, 2002). Multiple sources of personal influence are now internationally accessible to all, often within a virtual brand community, which is a specialized non-geographically bound, community on the Internet, based on social communications and relationships, among the consumers of a particular brand (De Valck et al, 2009, p.185).

The relationship between consumers and brands on social media requires ongoing research due to continuing developments in social media use. While consumer responses to brands include such concepts as loyalty, examined by Jacoby and Chestnut (1978); attachment, as discussed by Thomson et al (2005), and brand love, examined by many including Ahuvia (2005), Albert et al., (2008), Batra et al., (2011) and Fournier (1998), the constant development of social media tools continues to shape the psychology and behaviour of consumers when encouraged to interact with brands and artists.

This ‘two-step flow’ of communication and personal influence between brands and consumers, a model discussed by Katz and Lazarsfeld (1955) who stated “information, and thereby influences ‘flows’ from the media through opinion leaders to their respective ‘followers’” (Watts & Dodds, 2007, p.442) has become one of the key beneficial attributes of social media, in comparison to the previous, one-way, hypodermic needle model which mostly allowed little to no conversation between the two parties, treating individuals as “atomized objects of media influence” (Bineham, 1988).

One of the central ideas in marketing, as well as diffusion research, is that a minority of individuals who influence an exceptional number of their peers, known as influentials, are highly important to the formation of public opinion (Watts & Dodds, 2007, p.441). This concept continues to be defined by Facebook and Twitter users, understanding what is it to be influential on social media.

For instance, with regards to Twitter, many users believe that to increase their ‘followers’ is to increase their influence (Berinato, 2010), however to truly measure influence “one would have to take a combination of many metrics, including follower count, mentions, and re-tweets” (Berinato, 2010) to built a well-rounded understanding.

In models studied by Watts and Dodds (2007, p.444), “it is generally the case that most social change is driven not by influentials, but by easily influenced individuals influencing other easily influenced individuals.” Kiecker and Cowles (2002, p.313) further this idea stating that when facing unusual circumstances and unfamiliar issues or challenging decisions, individuals who are in search of the appropriate information will regularly turn to others within their social circle who are better informed on the subject, also known as opinion leaders. It is the perceived credibility of the source of the information that is a primary determinant of the influence the information communicates (Belch and Belch, 2001), also known as source credibility. This plays a role in the effectiveness of word of mouth.

In the online sphere, social media source credibility or the identification of true opinion leaders may be harder to find in traditional terms, but credibility may be derived from a “perceived trustworthiness, similarity, familiarity, and/or likability” (Myers and Robertson, 1972). There is a difficulty in online identification as people tend to participate in impression management, where they create a desired image of themselves or repair a damaged one (Goffman, 1967).

Opinion leaders “are both seekers and providers of marketplace information” (Hoyer et al, 2013, p.304) and are “more likely to derive their credibility from expertise and trustworthiness than from attractiveness” (Kiecker and Cowles, 2002, p.314) influencing the brand choices of consumers by credible word of mouth recommendations without vested interest in the product.

Similar to opinion leaders are market mavens, who encompass influence based on a more universal market expertise that is not product specific. This definition does not require them to be early purchasers of a product, not even necessarily users of the product about which they have information” (Feick and Price, 1987, p.85). It is due to their selfless motives that Market Mavens are perceived to be trustworthy because they do not stand to benefit from a consumer’s particular choice of product (Kiecker and Cowles, 2002).

“Purchase pals are individuals who accompany shoppers to the point of purchase” (Hartman and Kiecker, 1991, p.462) acting as their information source and influencing shoppers via their social support. Research undertaken by Kiecker and Hartman (1994) found that buyers look to purchase pals to help reduce the risk and uncertainty that is commonly associated with shopping for particular products or items.

Baumgarten (1975, p.12) stated that “earlier adopters have generally been found to be more influential than later adopters”. The notion of innovators and early adopters is that these individuals are deemed influential personal sources due to their personal experience with new products (Kiecker and Cowles, 2002). Mostly sought within a marketing environment, innovators and early adopters could include influential persons, experienced in finding the next big artists within the Music Industry, for instance bloggers or A&R staff.

Whilst surrogate consumers do not follow the typical conventions of word of mouth, due to the compensation they often receive for their services, the communication they offer is deemed to be independent of the marketers. By definition, a surrogate consumer is “an agent retained by a consumer to guide, direct, or transact marketplace activities” (Solomon, 1986, p.208).

Alongside Kiecker and Cowles’ five forms of word of mouth are Cialdini’s (1984) six principles of influence that are empowering practices that strengthen the possibility of influencing others. These include firstly, reciprocity which is the idea that a person should try to repay what others have provided to them as a future obligation. Secondly, commitment and consistency, described as our desire to be consistent with the choices we make. Third is social proof; the idea of the appropriate behaviour being understood by the behaviour of similar individuals which will be discussed in greater depth later on. Liking, understood that we are more likely to be influenced by someone we know and like than those we do not know and do not like. The fifth principle of influence is authority, which is similar to social proof in that information from established authority helps society understand how to act in a given situation, and finally, scarcity, where potential loss mostly provides more motivation than a potential gain, if there is only a limited supply of something, its perceived value rises.

Word of mouth, the “flow of communication among consumers about products or services” (Westbrook, 1987), has been transformed by social networks such as Facebook and Twitter. Due to the influence of its online members, the social network supports advocacy (Lawer and Knox, 2006) through ongoing conversations and the sharing of opinions because “the customer is now an actor in a social system” (Kozinets et al, 2010). This furthers a breakthrough theory from the 1940’s and 1950’s by Katz and Lazarsfeld (1955), which found that “individuals are likely to be influenced less by the media, than by exposure to each other.

Kiecker and Cowles (2002, p.316) further classify the many forms of word of mouth within an Internet environment using four distinct categories: (i) spontaneous, (ii) quasi-spontaneous, (iii) independent or third party-sponsored and (iv) corporate-sponsored.

Spontaneous word of mouth relates to the use of personal email accounts or web pages by individual consumers, which allows a vast audience of consumers to be reached via the internet, with little to no cost or effort (Kiecker and Cowles, 2002, p.316).

Similarly, quasi-spontaneous word of mouth follows individual consumers offering their word of mouth, but differs due to the environments, which tend to be created or encouraged by marketers (Kiecker and Cowles, 2002, p.316). This could include online bulletin boards, forums or chat rooms; virtual communities transferring information.

Independent or third party-sponsored word of mouth focuses on special interest web sites, groups, organisations or associations that “represent a wide variety of perspectives on different categories of goods and services” (Kiecker and Cowles, 2002, p.316), not excluding interests, hobbies and activities.

Finally, corporate-sponsored word of mouth amounts to perceived word of mouth via commercial communication by businesses. With regards to this, Kiecker and Cowles (2002, p.317) discuss two different online tactics. Firstly, the monitoring of product discussions to manage the way information is shared, its quality and quantity, within these online environments. Secondly, individual experts or persons, real or replicated, are used in a scripted capacity to recommend goods and services to consumers visiting the corporate web site, imitating organic influence.

With social media still in its infancy, it is apparent that the role of personal influence will continue to rise to unrivalled importance due to online communication and behaviour as discussed by Miller (1999). Previous research by Arndt (1967), King and Summers (1970), and Herr, Kardes and Kim (1991) has consistently demonstrated that personal sources of information have a strong impact on the preferences and choices of consumers (Kiecker and Cowles, 2002, p.312). As social media users can offer recommendations to fellow consumers, influence “can occur at virtually no cost and spread rapidly, both within and beyond the virtual brand community” (Brodie et al, 2012, p.4).

Social Proof

Social proof is a concept discussed by a number of theorists, in particular, Robert Cialdini. As one of the six principles of persuasion developed by Cialdini, he defines social proof as the way individuals tend to determine their appropriate behaviour for themselves in any given situation is to examine the behaviour of others around them, especially similar others (Cialdini, 1993b). Further stating that it is a strategy that “influences people’s perceptions of certain actions as correct in a given situation to the degree that we see others performing it” (Cialdini, 2001, p.100).

The basis of social proof forms alongside Festinger’s (1954) social comparison strategy where Festinger claimed social comparison with those similar to ourselves helps us to identify how we are supposed to act in any given situation, going on to state that one’s own opinion is threatened when comparison to others who are divergent is made (Festinger, 1954). In short, social proof is a psychological process where people assume the actions of others similar to them so as to behave “correctly”. “Social proof exists because we group together in society” (Starak, 2014).

Sherif (1970, p.153) stated there was an overlap “between the rise of a social movement and the formation of small groups” so when prevailing circumstances were proven to be exasperated, subjects would move toward a new social formation. 

Much of social proof theory was formed against Muzafer Sherif’s experiment of social factors in perception (1935) where test subjects within a dark room were asked about the movement of a dot of light which was in fact, stationary. Regardless of their answer, the subjects would move to reach a consensus with the other subjects.

In the present, social proof is becoming a form of marketing, the idea of getting consumers or fans to share their positive experiences of a product to promote it to likeminded individuals as “people tend to behave as their friends and peers have behaved” (Festinger, 1954). Within an online environment, consumers are encouraged to make decisions similar to those of people in their social network as an illustration of social proof (Tuten, 2008, p.44). This influencing strategy targets the normative beliefs of individuals, encouraging them to follow and conform to the normative behaviour (Shearman & Yoo, 2007). In theory, if one person promotes their positive experience of a brand to another, it has the potential to create a ripple effect spreading from peer group to peer group.

On social media, Ahuvia (2005) states that “consumers who select “like” for a brand may do so to allow that brand to express their ideal or actual selves”. A form of self-identity is shaped every moment a user posts on social media and how they connect to others within their network. After all, consumption, be it online or in person, is “a self-defining and self-expressive behaviour” (Schau and Gilly, 2003). 

Group Norms

Group norms are the generally unwritten, unspoken rules set out “to regulate and regularize group members’ behaviour” (Feldman, 2001, p.47), serving as a form of expressive function for groups (Katz and Kahn, 1978), responsible for the uniformities of social behaviour (Hogg and Abrams, 1995, p.159).

Douglas (1995, p. 78) summarises norms as the explicit and hidden standards by which the group functions and behaves, while adding to this, Bonney (1974, p.448) states that norms “represent the expectations, aspirations, and hopes of the group as well as the recognition of the group’s limitations.” As stated by Brown (1990, p.42), systems of norms are found throughout every possible human group, whether they are the most structured of institutions or free flowing friendship groups. It is key to note that “only those behaviours that ensure group survival, facilitate task accomplishment, contribute to group morale, or express the group’s central values” (Feldman, 2001) have the potential to become a recognised group norm.

As stated by Brown (1990, p.42), groups behave uniquely, each holding different views and attitudes, viewing the world in a range of different ways. “Norms can provide the social justification for group activities to its members” (Katz and Kahn, 1978), be it in their attire, language, behaviour or other subcultural capital that helps to differentiate them from members of other groups.

Building on this, Douglas (1986) held that “the normative structure establishes standard meanings for language and other group events”, creating the exclusivities to a particular group; certain terms of phrase used within a group of hip-hop fans which would not figure in the vocabulary of punks, for example.

Group norms, which fall under social identity theory, often have a consistent, powerful influence on the behaviour of group members (Hackman, 1976). Tajfel first introduced social identity theory in 1972, with three stages of evaluation being categorization, then social identification followed by social comparison. 

The social categorization allows for the understanding of the social environment, be it through race, nationality, occupation or other. Social identification relates to the adoption of the group identity once it has been identified, for instance, identifying as a student and then acting in ways it is believed that students act, together with the emotional and valuable significance of it. Finally, social comparison relates to the comparison of the group to other groups by way of competition and potentially hostility, in order to reduce any uncertainty of the group’s opinions and abilities, seeking a positive distinctiveness, further defining the group identity.

Turner (1975) built on this, maintaining that social Identity depended on intergroup social comparisons that aimed to confirm or establish ingroup-favoring evaluative distinctiveness between ingroup and outgroup, motivated by the underlying need for self-esteem.

With reference to Bonney’s work and describing behaviour within the normative structure, Douglas (1986, p. 64) stated that there are behaviours at the outside of the group that are deemed to be different, that could bring reward or punishment depending on whether the group sees these behaviours as being positive or not for the group at that time. Williams, Martin and Gray (1974, p.262) held that these behaviours are often then appropriated, themselves becoming a norm of the group. “Interpersonal influence leads behaviour to converge on a group norm; the norm is then internalized by the individual”.

Accepting and acting upon group norms offers its members validation and reassurance within that group, the reduction of risk, added security and the encouragement to others to conform (Douglas, 1986, p.65).

Inconsistencies between group norms and behaviour may unveil the difference between the perception and the reality, a “dichotomy between what the group is really like and how it would like to be perceived” (Feldman, 2001, p.50). This idea may be attributed to ‘self-image’, whereby an individual behaves differently to how they would like to be seen by others. Goffman (1955) described this as a ‘face’ that each person presents to other members of a group, and it is no different online with an online identity or ‘online self’.

Rimal et al. (2004), discussed an example of this whereby students who perceive themselves as drinkers are more likely to consume alcohol, as well as being more influenced by their perceived frequency of consumption, compared to those who may perceive themselves as non-drinkers.

Optimal distinctiveness theory, which seeks to understand the ingroup and outgroup differences was discussed by Brewer (1991, p.581), who identified that two opposing needs, the need for assimilation and the need for differentiation, must be compromised for social identity. This idea affects the type of group an individual may relate to based on their fundamental needs. However, what happens when an individual no longer feels connected to a particular group?

Discussing the behaviour of those within a group who deviate from the group’s norms, Douglas (1986, p.172) offers the possible outcomes to be the acceptance and conformity of the norms, the attempt to change the norms in their favour, the acceptance of a deviant role or to leave the group. When deviant behaviour is observed and consequences follow, it reminds other members of the group of the behaviour that is acceptance within that group, a way of reaffirming behavioural norms. “When groups punish norm infraction, they reinforce in the minds of group members the authority of the group” (Feldman, 2001, p.49). There is a greater pressure for conformity within a group that illustrates a strong cohesion to their group identity, as the solidity of that group is very much dependent upon the desirability to the group. This can only occur if there are high levels of satisfaction available from being a member of the group (Douglas, 1986).

Despite discussing group norms in a physical setting, through subcultural groups; their behaviour, beliefs, language and so on; group norms and normative structures are readily found within the online community. A prime example of this being One Direction fans who have a great sense of community with their fellow fans, a strong solidity to their group identity and who regularly appropriate a particular hashtag on Twitter to communicate and support their group identity. Within the online community, group norms will continue to influence a member, in their use of language and online behaviour for instance, especially on social media.

Be it online or offline, group norms allow its members to understand what is expected of them, enabling them to anticipate the actions of their fellow group members and prepare the most appropriate response in a timely manner (Feldman, 2001, p.48), Hogg and Tindale (2005) describe group norms as the “shared patterns of thought, feeling, and behaviour”, helping to bring a sense of belonging, protection and community.


Research is defined within the Oxford dictionary as “the systematic investigation into and study of materials and sources in order to establish facts and reach new conclusions” (Oxford English Dictionary, 1989). In short, it is the process of developing ideas, to understand truths from expanding on former investigations or by a fresh approach.

The main types of research are primarily quantitative, qualitative or a mixed method of the two. To distinguish between qualitative and quantitative, Punch (2005) gives the basic definition that quantitative research is “in the form of numbers, and qualitative research, not in the form of numbers”. Expanding on this, quantitative research depends on stringent means of defined measurement, a “measurement of frequency of phenomena in the social world” (Schwandt, 2001). Whilst quantitative research is dependent on a choice of set figures, qualitative research seeks to describe or translate the problem whilst somehow coming to terms with what it all means (Schwandt, 2001). Bryman states that “qualitative research is deemed to be much more fluid and flexible than quantitative research in that it emphasizes discovering novel or unanticipated findings” (Bryman, 1984).

For this research assignment, the quantitative research undertaken will be a range of questions created by my findings in the literature review and directly linked to my theoretical framework, undertaken using Survey Monkey; an online survey resource. 
Bell (2010, p.158) examined the importance in understanding the different question types; their advantages and limitations, as well as being sure that the information needed will be produced through the created questions, also stating the need for the responses to be analyzable.

Within the survey, Likert-type questions will be used, whereby the participants will have a range of statements to read and they must select to what extent they agree with that statement across a seven-point scale. Likert-type questions are used to attain the participant’s degree of agreement or disagreement of a particular statement by way of a psychometric response scale (Bertram, 2007) and are the most widely used approach in survey research for scaling participant’s responses. The options available will range from strongly agree, agree, neither agree or disagree, disagree or strongly disagree as part of the ordinal data. This will measure the participant’s attitudes or feelings to the concepts investigated in this research and this data will be transformed into codes, which can then be displayed as a range of charts and tables to further illustrate the findings. 

The conceptual framework was built around the literature review to test the discussed notions of influence, social proof and group norms within the social media environment, whether these concepts have a resounding effect on the behaviour of Facebook and Twitter users with regards to ‘liking’ or ‘following’ bands or artists online. The conceptual framework allows the relationship between social media users and a range of metrics to be investigated.

Following the conceptual framework, the data collected was coded accordingly to reflect each concept, which can be seen in Appendix 1. This was to ensure that there were adequate questions covering each research concept and where concepts were under-represented in the questionnaire, new questions could be formed.

Coding is the process of labeling and then categorizing data, condensing the data so that it can be counted to produce means and standard deviations furthering statistical analysis (Evans, 2007, p.176) and identifying patterns by pulling themes together (Punch, 2005). As an example, each of the seven Likert scale options per survey statement was given a number, with the quantity of selections for each Likert scale option being used to calculate the general trend of data by way of an average and standard deviation.

This sample, made up of 140 respondents to gain the largest, most varied sample as practicable, was a representative of the population of Facebook and Twitter users, as it is was not possible to offer the survey to every single Facebook and Twitter user. The results of the survey are deemed a purposive sample due to my selection of participants, according to the restricted criteria set; Facebook and Twitter users. Following this, the results of the data were then analysed, presenting the descriptive statistics in a manner that allowed for simpler interpretation of the data to then be expressed in a range of charts and tables to visually express the findings.

The questionnaire comprised of two parts. The first was to gain an understanding of who the participant is by way of their demographic, which social media platforms they use out of Facebook and Twitter. The second section discussed each concept researched; influence, social proof and group norms, using the Likert-type questions to rate and formulate an understanding to the strength in which participants agree to particular statements. It contains 15 questions in total.

The advantages of Likert-type questions comprise of an average being taken from a question’s answers to easily quantify results, as well as the Likert scale being a universally recognised method for data collection. Using a quantitative research method such as Likert-type questions will result in the depiction of typical and atypical social media behaviour, by showing the level of difference between participants’ opinions. The likelihood of the findings being representative for an extended population of social media users can then be determined by the quantity of participants selecting a particular level of the Likert scale, whether they are a large majority or whether participants opinions are split across a variety of the seven-point scale. A large majority selecting one scale option, for instance that they strongly agree to a statement, would offer a clearer depiction of social media users opinion regarding that statement, compared to participant scale selection being fairly evenly distributed across multiple scale options.

The main limitations that were faced in this research were mostly due to the nature and size of the purposive sample; a sample in which something is already known about the specific people and particular ones are selected (Denscombe, 1998, p17). With the aim of having 140 respondents compared to the large numbers of Facebook and Twitter users, there was a risk that the data collected would be skewed by bias or deviation due to the purposive sample size. Another limitation is that with seven potential options of agreement for the participants to choose from, the 140 respondents may have been split across multiple points on the scale, meaning there would be no clear understanding of social media users opinion on the particular statement, unless a majority percentage was found.

There was also the matter of ethics to be considered. Since the research is dealing with personal information, an ethics form was completed and approved prior to the creation of the survey to explain its nature, its purpose, methods and any potential risks. Regardless of the data collected remaining anonymous, the participant always had the right to withdraw from the online study at any time.

To ensure the questionnaire offers fair, open questions that do not lead toward a particular answer, and to ensure that the questionnaire functions well (Bryman, 2001), a pilot study was undertaken whereby feedback from participants was received and taken on board relating to the clarity and fairness of the questions asked, to better strengthen the resulting data and avoid skewed results. From the pilot study of 10 participants, it was found that the questions were fair, easy to interpret and did not lead heavily towards a particular answer so no changes were needed. The questionnaire can be seen in Appendix 2.

The questionnaire was created using online survey site eSurveyCreator. During creation, the website allows the reordering and editing of questions, helping the process of presentation and flow of questions. It offered an automatic collation of results, which meant analysis could be done without having to manually enter data into a spreadsheet to calculate averages and the standard deviation, saving time and ruling out human error.

Using eSurveyCreator also ensured an ease of sharing the survey online with a simple web link that could be posted on Facebook and Twitter to encourage social media users to participate. Once posted on Facebook and Twitter, several friends and ‘followers’ shared the link to the survey, which helped expand the results to a wider sample of social media users.

The survey was available for completion online for a total of ten days to give enough time for a wide variety of Facebook and Twitter users to see and complete the survey. When a tweet was sent out regarding the survey, it was retweeted by a few Twitter users that meant new participants saw the survey from a secondary source and at a later date. Similarly on Facebook, 5 friends shared a post regarding the survey that drew in new participants from a secondary source, days after the survey was created.



The hypothesis of the research was to test social media users’ behaviour with regards to bands and artists in relation to their social peers, to further understand whether likes and ‘followers’ truly represent the popularity of a band or artist, or whether concepts of social proof or group norms influence users. Each Likert-type question directly related to understanding why social media users ‘like’ or ‘follow’ bands or artists on Facebook and Twitter.

Results did not provide clear answers to the questions and therefore this research, often produces conflicting answers between participants who agreed and disagreed with statements. Much of this may be due to the participants’ individual behaviour on social media, whether they heavily engage with bands or artists on social media, as well as their perceived value of likes and ‘followers’ as online metrics.

In total of the 140 participants, 55.7% were male, 43.6% were female, with 0.7% preferring not to specify their gender. This presents an issue of gender bias in favour of males despite an equal opportunity for both sexes to be involved, which along with the purposive sampling method, may somewhat skew the findings.

Equally, there was a disproportion with regards to the age ranges of the participants with 48.6% being between 19 and 25 years old. Since many in the purposive sample were fellow University students, friends or peers of a similar age, it was to be expected that this particular age bracket would be a larger proportion of the participants than the others, especially as 35% of Twitter’s user base for instance, 95 million users, are between 18 and 29 years old (Apuzzo, 2014).

115 participants, 82.1% of the 140 respondents had both a Facebook and Twitter account allowing them to answer all 15 questions. 

The first item using a Likert-type scale to gauge agreement was the statement “I am more likely to like a band or artist on Facebook if my Facebook friends like it”. There were 123 participants answering this question despite 138 participants stating they used Facebook, which raises issues on how clear the survey was in its creation or that questions were simply missed out when they should have been set to compulsory for the participant to move on to the next question. Should further research be conducted, questions would be set to compulsory and this issue should be resolved.

Results were mixed, with 17.07% strongly disagreeing with the statement, 22.76% disagreeing, yet 26.83% agreeing somewhat. The inconsistency of the results shows the importance or lack of importance in social proof and group norms to the individual participants. With the way Facebook shares the real-time online activity of friends on the scrolling news ticker, it was wrongly expected that a larger percentage would agree to the survey statement, as the natural curiosity of seeing friends ‘liking’ a particular profile page would be expected to lead to a user investigating that page and potentially ‘liking’ it.

This survey item would have been more effective if it was known how many artist profiles each participant liked on Facebook and how often they ‘like’ a new artist’s profile, for those participants who disagreed or strongly disagreed may not tend to ‘like’ artist’s profiles on Facebook often or at all.

The next statement related to the perceived popularity of artists by Facebook users and whether that influenced users with, “I am more likely to like a band or artist's page on Facebook if it has a large number of likes”. 38.71% disagreed with this statement and 27.42% strongly disagreed. This shows that Facebook users aren’t influenced to ‘like’ a Facebook page solely because it has a number of likes, disproving notions of Social proof influence on Facebook. While self-discovery of new music is important to many rather than solely liking music because it is popular, it was expected that most would agree with this statement and the concept of social proof, however, the research denies this. 

Perceived popularity was further examined in question 6 with the statement, “The more likes a band or artist has on Facebook, the more popular that band or artist is”. Likes have often been used as a metric for bands and artists to quantify their popularity ever since MySpace was at the height of its popularity. Results for this question appeared contrasting. While 29.03% agreed somewhat and 20.16% said they agreed with the statement, 20.97% disagreed somewhat.

My expectations were that a majority would agree to the statement as the number of likes achieved is typically considered an appropriate metric for engagement (Hoffman and Fodor, 2010) and subsequently, popularity. Compared to Twitter ‘followers’, Facebook has typically tended to be a more honest indication of popularity by way of likes, but these results appear to indicate that opinions are split, possibly signifying a shift in what Facebook users believe page likes to actually mean.

To advance investigations into the link between the quantity of likes and popularity, further research should be obtained into how many profile likes would social media users deem to signify a truly popular band or artist or whether other metrics, such as status or photo and video likes, or how many social media users are talking about a particular band or artist, are a more factual illustration of popularity.

Question 7 relates directly to concepts of social proof and group norms; “If a member of my social group likes a particular band or artist on Facebook, I am more likely to like them on Facebook myself”. 27.42% of participants agreed somewhat with this statement while 24.19% disagreed. These findings do not give a definitive attitude towards the concept of social proof with regards to the ‘liking’ of bands or artists as was to be expected. It appears that the encouragement of users to make decisions that mimic their social network peers, as discussed by Tuten (2008, p.44), does not follow conclusively with regards to ‘liking’ bands or artists on Facebook, rather a case-by-case basis.

Further research as to what qualities a member of a social group has to have to influence a Facebook user to ‘like’ a particular band or artist would offer more clarity with regards to social proof influence, for instance, concepts of trustworthiness and taste may feature. 

The statement in question 8, "I am more likely to like a band or artist on Facebook if someone I know who is knowledgeable about popular music likes it" resulted in 29.84% of participants agreeing somewhat and 20.97% disagreeing. The conflicting results of this question could relate to the participants understanding of what popular music is considered to be, whether they have Facebook friends who they deem to be knowledgeable about music depending on their passion for seeking new music, or simply that those who disagreed are not influenced by fellow Facebook friends in this capacity. However, for those who did somewhat agree, it shows the influence of opinion leaders to some Facebook users and the credibility from expertise and trustworthiness that Kiecker and Cowles (2002, p.314) discussed. A further detailed exploration would be recommended to question the traits of those knowledgeable about popular music with regards to the influence they exert on social media users, as well as a more general investigation into where social media users hear about new or popular bands and artists on social media. 

Question 9 asked the participants to select their level of agreement to the statement, “Band or artist pages that I like on Facebook are a true representation of my favourite bands or artists” with results being fairly conclusive with 27.42% agreeing somewhat and 25.81% agreeing. This supports the research of Ahuvia (2005), that consumers who choose to ‘like’ a Facebook page of a band or artist, do so to express their ideal or actual selves, rather than engaging in impression management to create a desired image as discussed by Goffman (1967).

Question 10 changed the focus from Facebook to Twitter with participants selecting their level of agreement to the statement “I am more likely to follow a band or artist on Twitter if they are followed by those I am following”. There were 120 participants despite only 117 of them stating they had a Twitter profile which again raises issues of the design of the survey, how clear it was for participants and a better use of compulsory questions to move on to the next question to ensure each item is answered correctly.

While 21.67% agreed somewhat to this statement, 0% strongly agreed with the statement, as well as 29.17% disagreeing and 15% strongly disagreeing. The use of Twitter between fans and artists or bands is considerably different to that of Facebook, with fans more likely to un-follow and re-follow bands or artists on Twitter over time compared to the more permanent state of Facebook likes. While Facebook concentrates towards connecting users with real life friends and family, Twitter is often utilised by ‘following’ those with no personal connection to the user at all, so the social proof or personal influence to the user solely depends on the credibility of those a user ‘follows’, deriving from, as Myers and Robertson (1972) discussed, perceived trustworthiness, similarity, familiarity, and/or likability. The survey results were expected due to the known difference in behaviour of Twitter users compared to Facebook users.

To further this research, notions of trustworthiness, similarity, familiarity, likability and others could be tested to highlight what traits are most important to Twitter users in a descending order from most important to least important. As well as this, a more general question could explore the bands or artists that participants ‘follow’ and their relationship; why they were ‘followed’ and what in particular influenced them to ‘follow’ them.

The next statement, “I am more likely to follow a band or artist on Twitter if they have a large number of ‘followers’” brought resounding results with 45% disagreeing with the statement, and 25% strongly disagreeing signifying that the quantity of Twitter ‘followers’ a band or artist has, has no influence on a user ‘following’ them, again disproving notions of social proof influence, on the Twitter platform. Similar to the findings under question 5, this answer was unexpected. However, this could be due to the fact that Twitter ‘follower’ metrics tend to mean less than Facebook profile ‘likes’ as the profiles a Twitter user ‘follows’ can change far more rapidly than those profiles a Facebook user likes, so Twitter ‘followers’ are a constantly fluctuating metric. This shows that Twitter offers less social proof influence to users with regards to the ‘following’ of band or artist profiles.

The statement in question 12, “The more ‘followers’ a band or artist has on Twitter, the more popular that band or artist is” ended in mixed results. Whilst 30% agreed somewhat to the statement, the remaining percentage was split relatively equal across the rest of the scale. Covering the concept of social proof influence, it was expected that participants would have mixed views on this question. Some band or artist profiles, especially those of bigger artists, are merely a source of news relating to that band or artist, compared to other bands or artists who use Twitter regularly as a platform for directly communicating with fans and discussing a range of topics, not solely relating to their music.

To improve the clarity of the results, this question could be broken down and further investigated by asking participants how many ‘followers’ a band or artist’s profile must have for them to be deemed popular, or what elements of a profile do they believe affects the perceived popularity of a band or artist, for instance the quantity of retweets or favourites on a post, shared photo or video. 

Question 13 asked participants to offer their level of agreement to the statement, “If a member of my social group follows a particular band or artist on Twitter, I am more likely to follow them on Twitter myself”, which was centred around the concept of group norms and the influence it offers. While 21.67% agreed somewhat to the statement, a larger percentage of 25.83% disagreed, giving a conflicting significance to the results. It appears that the acceptance and acting upon group norms by way of ‘following’ the same bands or artists on Twitter as members of your social group, does not follow the same consistency needed offline for validation of a particular group. It would provide interesting insight however, if this question was posed to members of online communities or fandoms, such as those who ‘follow’ One Direction, as results within fan communities would be expected to prove conclusive compared to that of mere social groups.

To enhance the clarity of these results, further scrutiny of the qualities or characteristics a group member must have to influence another member should be investigated.

Question 14 was answered by 119 participants, despite only 117 stating they had a Twitter account, which, as mentioned before, illustrates a problem with the design of the survey.

For this question, influence and social proof are addressed with the statement, "I am more likely to follow a band or artist on Twitter if someone I follow, who is knowledgeable about popular music, follows them". Results were fairly evenly distributed with 23.53% agreeing somewhat to the statement, 21.01% disagreeing and 19.33% neither agreeing nor disagreeing.

The conflicting result to this statement compared to that of the statement in question 8, highlights the differences between Facebook and Twitter. It is expected that Facebook users are more likely to ‘like’ Facebook profile pages of bands or artists, than Twitter users are to ‘follow’ bands or artists, as Facebook offers a more definitive online representation of what a user likes as the social platform is heavily built on the function of ‘liking’ statuses, pages, etc. Twitter on the other hand focuses more on the communication of tweeting between users with their company mission statement stating that Twitter helps create and share ideas and information instantly (Twitter, 2015).

Again, the term ‘popular music’ within the statement could mean different things to different participants, so to improve this research; the term should be defined to make it clearer to participants. It would also provide depth to this question, if a question featured prior to this one asking participants what characteristics were needed to make an individual knowledgeable about popular music, to lead into this question. 

The final question posed the statement, “Bands or artists that I follow on Twitter are a true representation of my favourite bands or artists” with 27.50% agreeing somewhat and 25.83% agreeing. This shows that while Twitter users may or may not ‘follow’ many bands or artists on the social media platform, those that they do ‘follow’ are their favourites. This affirms that a band or artist’s quantity of ‘followers’ are a good representation of their popularity but not necessarily a true representation, as it depends on the band or artist’s usage of their Twitter platform.

This research has shown the subtle differences between the influence exerted on Facebook compared to Twitter, with regards to online group norms, due perhaps to Facebook users connecting with people they already personally know, compared with Twitter users who often ‘follow’ those they do not personally know.

Results indicate that Facebook likes and Twitter ‘followers’ are deemed to be good metrics of popularity with both survey statements regarding Facebook and Twitter band or artist pages that a participant ‘likes’ or ‘follows’, being a true representation of their favourite bands or artists.

More research is needed to break down these metrics to further understand at what figure do users deem popularity to truly begin and considering this research demonstrates that a large number of likes or ‘followers’ may be a symbol for popularity, it appears to have little to no effect in influencing users to ‘follow’ or ‘like’ a band or artist online. This latter point is something unexpected from the research; that the number of likes or ‘followers’ means very little to the participants.

The limitations of gender bias, disproportion in the range of ages participating and the clarity of some of the questions may affect the validity of the findings, but despite this, the results give a good indication of social media users acceptance of influence online depending on the influencer and how online group norms differ from those in person. With the likelihood of social media and the behaviour of social media users regularly changing, further ongoing research is recommended to give a honest, up to date comprehension to what likes and ‘followers’ mean, as well as how users are best influenced by their peers.

This research has contributed to the music industry, bands, artists and social media users in identifying that while the bands or artists that social media users ‘like’ or ‘follow’ are indeed a true representation of their favourite bands or artists, a high number of Facebook profile page likes or Twitter ‘followers’ does not exclusively represent popularity nor does it influence social media users to join those large numbers. 

With so many independent bands or artists looking to gain large numbers of likes or ‘followers’, it is important that they understand what social media is good for; a closer communication between them and their potential and actual fans, a connection that can enhance the probability of fans becoming truly invested in their careers at a physical level, a psychological level and culturally specific level; keen to promote their music via the five forms of word of mouth discussed by Kiecker and Cowles (2002) to their peers.

It would provide fascinating data if further research was to investigate what characteristics a social media user has to have to influence another social media user, whether known personally or not, as well as considering which elements within a band or artist’s social media page creates the most influence to social media users. With social media users readily more influenced by visual marketing than solely text-based marketing, understanding what areas prove most influential on a social media page would broaden the understanding built by this research to cater for improving the music industry’s usage of social media pages for bands and artists.


The data deduced from this research has shown that on both Facebook and Twitter, users consider the quantity of page likes or ‘followers’ a band or artist has, indicates their level of popularity but that users are not influenced to ‘like’ or ‘follow’ them simply by the number of likes or ‘followers’ they have. 

Theories like social influence are complex due to the individualistic differences in human behaviour, so it was no surprise that social media use was found to differ greatly from user to user. Within this research, it was discovered that influence from members of a users social group did not bring clear results. For Facebook, 27.42% are influenced by their social group to ‘like’ a band or artist’s page, but 24.19% are not. For Twitter, results were similar, with 21.67% who are influenced and 25.83% who are not.

This research benefits the music industry as to the perception that a quantity of likes or ‘followers’ can give. It also highlights that word of mouth on both Facebook and Twitter is not necessarily enough to gain the attention of those who do not ‘like’ or ‘follow’ a particular band or artist.

There were limitations within this piece of research due to an unequal representation of genders and age ranges from the purposive sample. To improve this, a larger survey with each gender and age range represented fairly would provide a more factual depiction of social opinion. Furthermore, the survey results could be enhanced by the use of additional questions asking of the likelihood of ‘liking’ or ‘following’ a particular band or artist at different numerical milestones, along with identifying what characteristics are most effective for a participant’s social group member to influence them to ‘like’ or ‘follow’ a particular artist profile on social media.

Further research is needed to investigate the influence applied to a user by their Facebook or Twitter friends, and what particular aspects on social media platforms provide influence. This would help bands and artists in the Music Industry to focus their attention on those who have yet to ‘like’ and ‘follow’, expanding their social media audience, whilst still ensuring to communicate with those who have already connected. 

This research is important to researchers and practitioners as studies of influence theory with regards to new technologies, such as social media, are sparse and with social media user’s behaviour evolving alongside the ongoing development of technology, further research would provide fascinating data on the behaviour and illustration of the online self.

Expanding upon this study, future research into the characteristics or qualities that a member of a social group must possess to influence a fellow social media user to ‘like’ a particular band or artist would offer useful clarity to social behaviour online. More interestingly, it would provide fascinating insight to compare Facebook and Twitter page likes and ‘followers’ for bands and artists to the amount of albums sold and streams to question the link between social media fans and those who purchase their music in support, offering valuable insight for those working within the Music Industry. 

Finally, with such regular design changes on social media, ongoing research would be useful to continually measure attitudes and the changes in social media behaviour of users through future trends.


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Do social media likes & followers = popularity? - Sunny Stuart Winter


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