Ozzie Sport

I know I haven’t posted an update on how my lit review is going but it is going. At the moment, it mostly consists of tossing citations together about teams in order to get a better picture of the fanbase for particular clubs and how that has evolved over time.

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Review of Literature

The review of literature will define what fans and sport fandom are, and examine how sport fans show allegiance to clubs they barrack for. The definitions of fandom and fans are key to understanding how and why people express interest in a team online. After that, the lit review will look at population studies of and characterizations of sport fandom in Australia.

The Definition of Sport Fandom

There are very few works that focus on the definition of fandom as it pertains to sport. Most literature presupposes that its readers understand what the concept means and then proceed to examine some aspect of sport fandom. While researching sports fandom and its definitions, four different groups were identified as offering their own perspective on how to identify and define fandom. The first group includes sports marketers and managers, who broadly speaking, define sports fandom around potential for spectatorship. The second group involves sports sociologists and historians; they tend to define sports fandom as a form of identity and as a product of a specific culture. The third group involves the media and sports fans, where the definition involves the expression of allegiance to a club that is often grounded in the moment or the short term. A fourth group was identified as doing research about sport fandom. This group includes popular culture studies academics, who tend to focus on fan interaction with the team and the game, and who focus on sport fandom as a smaller subcomponent of fandom.

Sports marketers and managers.

Stewart (1983) wrote for an audience of VFL fans, while providing a great deal of information regarding the organization of the league, its financial situation and other information that would be of more interest to people interested in sports marketing. Fans are frequently described based on their proximity to stadiums, training grounds and the location found in a team’s name. These descriptions were used to explain the potential for spectatorship: “The Club has little local support — there are few private dwellings in the vicinity — and most of its supporters are centred in the outer south-eastern suburbs.” (p. 41) In a few cases, fans are all described based on their economic status and how fans of other teams perceive them: “It is thought that while the affluent eastern suburbs residents are appreciative of the team’s success, they prefer to spend Saturday afternoon in active leisure activities like tennis or gardening.” (p. 40)

Shilbury, D., Quick, S., & Westerbeck, H. (2003) published a book about sports marketing. Much of the content is focused on fans from the perspective revenue for a club, league or sport converting them into spectators and consumers of merchandise related to the organization and its sponsors. The authors do not create their own definition of fan. Rather, the authors (p. 70) borrow from Smith and Stewart (1999) to define categories of fans: passionate fans, champ followers, reclusive partisans, theatergoers and aficionados.

Sullivan (2004) wrote for an audience of potential sport marketers. The author said “the term fan will be used in the broadest sense and will, therefore, imply a range of attachments.” (p. 131) Sullivan then characterized fans as spectators and consumers of various media who could be profiled using three key factors: Geographic, demographic and behavioral factors. The discussion around these factors involved how they impacted the potential for spectatorship and the consumption of media related to a team.

Nicholson (2004), a sport management academic, wrote to reflect on the problems the AFL faces in terms of becoming a national game. The geographic population imbalance between clubs in Queensland and New South Wales compared to Victoria was a major problem: The league was not balancing team location with population areas, nor was it financially sponsoring player development. The author rarely used the word fans to describe these problems: Spectators, the market and television audience are used instead.

Sports sociologists and historians.

Collins (2005) wrote for an audience interested in the history and evolution of several football codes in Australia. In describing a proposal to merge rugby league with Australian rules football, the different codes were described as appealing to two different views about Australia’s place in the world: transnational versus nationalistic. These differences point to a definition of sports fandom relating to identity.

Like Collins, Cashman (2002) was writing for an audience of those interested in history. Cashman (2002) differs in that his history focused on more on the connection between Australian sport and other issues in Australian life including identity, culture and parallel Australian history. Both authors connected sport to national identity. In the case of Cashman, the term fan is almost never used in the text. Words like crowds, interest, Australian with adjectives further identifying spectator culture and sport participants are used instead. Again, the author’s undefined use of fandom involves identity.

Adair, D. & Vamplew, W. (1997) are sports historians that tried to debunk some historical myths about sports culture in Australia. One of these myths involved the defining of Australians as sports obsessed. This definition, where fans are defined as people obsessed with sports, is reinforced by talking about match attendance compared to the total population, and by the consumption of sport on television. Spectatorship plays a role in the definition with less frequency than that of the identity of a nation obsessed with sports and as an important component of Australian popular culture.

The media and sport fans.

Sport fans and the media often talk about fandom on a personal level or to describe their actions around the short term.

Popular culture studies academics.

Popular culture studies scholars like Jenkins (2006) offer the last definition. They define fans as an active population who engage in activities related to an object produced by the larger popular culture. This production includes activities like writing fan fiction, creating costumes, producing fanvids and organizing conventions. Popular culture academics also define fans as posessing a sense of ownership of their product that is removed and distinct from the official one, that they view actors, athletes, copyrighted and trademarked materials as communally owned by fans.

Population and Characteristics of Australian Sports Fandom

While there are many definitions and underlying assumptions as to what a fan is, there has been less work done looking at what makes these communities demographically distinct from populations. Much of the work done approaches the issue from the perspective of comparing the population of different sports or leagues. When specific clubs are looked at, the literature tends to focus less on research done about fans of those teams than it does on repeating traditional narratives about fan allegiances that may date back one hundred years.

Sports.

Delpy & Bosetti (1998) conducted a demographic study of sports fans online that found sports fans were 6% more likely to be female (36% compared to 30%) and were 1.3 years older (34 compared to 32.7) than the whole population of the Internet.

Adair, D. & Vamplew, W. (1997) cite a study that found that during the 1970s, 28 percent of men and 21 percent of women in Australia regularly attending sporting events as spectators.

The VFL and AFL.

The VFL and AFL have been attributed with having historically high levels of female fans, both as spectators and barrackers, when compared to other football codes in Australia and around the world. In the early days of the sport, female spectatorship was between 30 and 50 percent. (Cashman, 2002, p. 48) This contrasts with Australian, specifically New South Wales, rugby which is characterized as being conservative, middle class, patriarchal and often containing strains of misogyny that discouraged the growth of female spectatorship. (Cashman, 2002, p. 52) Both codes were characterized as having large white spectator bases. (Cashman, 2002, p. 56)

Characteristics of sport fan communities can differ by club. A survey of research done about VFL/AFL teams reveals some of these different characteristics.

The Fitzroy Lions, who eventually became the Brisbane Lions, were originally from an area where their fanbase drew heavily from a population middle-class white-collar workers. (Shaw, 2006, p. 115) During the 1940s, Fitzroy Lions were similar to their counterparts at Collingwood and North Melbourne in terms of fan composition. Shaw (2006, p. 79) characterizes them as being drawn from the working classes and prone to violence similar to that of future British football hooligans. The 2009 team ranked second for total fans, with 861,000 fans. (Roy Morgan Research, 2009, July 19).

Early in the history of the Carlton Blues, most of their fans were from the Carlton area and represented the major population found there: “middle-class white-collar workers and the occasional silvertail.” (Shaw, 2006, p. 115) The Carlton Blues had one of the largest fan bases during the 1940s. According to Shaw (2006, p. 101), they could draw crowds irrespective of their on-field performance. The 2009 team ranked seventh for total fans, with 493,000 fans. (Roy Morgan Research, 2009, July 19).

In the period around the Magpies founding in 1892, fans were characterized as being bootmakers and working in the footwear industry. (Grow, 1998, p. 69, 77) During the clubs early part of the 20^th century, the Collingwood Magpies fans were predominantly from Collingwood. They matched the characteristics of the neighborhood: Semi-skilled members of the working class that were mostly Irish Catholics. (Shaw, 2006, p. 115) The Collingwood Magpie fans are characterized as having “strong working-class origins”. (Stewart, 1983, p. 35) The club has historically enjoyed strong local support, both in terms of developing a fan base and with local businesses. During the early part of the 1900s, 70 percent of the club supporters were local and 80 percent were members of the working class. (Sandercock, 1981, p. 199) In the decade around 1900 to 1910, fans were described as being drawn from the working class. (Shaw, 2006, p. 79) During the 1940s, the club had one of the largest fan bases in terms of game attendance. According to Shaw (2006, p. 101), the team could draw crowds irrespective of their on-field performance. There was a demographic shift by the 1970s, with over 50 percent of the local population being not native born and Anglo-Irish-Australian; instead, the local fan base was composed largely of Southern Europeans. (Sandercock, 1981, p. 200) The characterization of working class values continued on despite these changes. According to Roy Morgan Research. (2009, July 19), the modern team has the third largest AFL fan base, with over 731,000 fans.

During the 1870s and 1880s, Essendon was one of the three big clubs in terms of the number of paying fans. (Grow, 1998, p. 55) During the early part of the 20^th century, Essendon Bombers fans were drawn from the local area and fans were mostly from the lower middle-class. (Shaw, 2006, p. 116) Essendon Bomber fans are from the “moderately affluent north-west suburbs” who have a reputation “for being conservative and responsible.” (Stewart, 1983, p. 36) The team has the fourth largest AFL fan community with 638,000 barrackers. (Roy Morgan Research, 2009, July 19).

During the 1870s and 1880s, Geelong was one of the three big clubs in terms of the number of paying fans. (Grow, 1998, p. 55) The team has the eighth largest AFL fan community with 488,000 barrackers. (Roy Morgan Research, 2009, July 19).

The Hawthorn Hawks fans are characterized as being from the affluent eastern suburbs, but who would are not as interested in attending matches as fans of other teams. (Stewart, 1983, p. 40) The 2009 club ranked tenth in the AFL for most fans, with 381,000. (Roy Morgan Research, 2009, July 19).

The Melbourne Demons are characterized as not being able to draw local support, with most of the team barracking for the team being “centred in the outer south-eastern suburbs.” (Stewart, 1983, p. 41) The team had the fewest people barracking for them of any team in the AFL during the 2009 season; only 187,000 people identified themselves as fans in research conducted by Roy Morgan (2009, July 19).

The North Melbourne Kangaroos fans during the early part of the 20^th century are described as being from the working class and being a precursor of the British football hooligans. (Shaw, 2006, p. 79) During the 1920s, the fanbase had a noticeable amount of butchers. (Shaw, 2006, p. 83) The 2009 club ranked second to last in the AFL for most fans, with 219,000. (Roy Morgan Research, 2009, July 19).

At the Richmond Tigers founding in 1885, fans were characterized as being larrikins who threatened the club’s existence by keeping away paying customers. (Grow, 1998, p. 72) During the early 20^th century, Richmond Tigers fans were mostly semi-skilled Irish Catholic members of the working class. (Shaw, 2006, p. 115) The Richmond Tigers supporters are characterized as “defiant and arrogant.” (Stewart, 1983, p. 42) Prior to the 1950s, being born in Richmond meant being a Richmond Tigers fan. This pattern of fans being located close to the historical home of the team changed with in the post war era. (Sandercock, 1981, p. 183) The 2009 team ranked ninth for total fans, with 392,000 fans. (Roy Morgan Research, 2009, July 19).

During the 1870s and 1880s, South Melbourne was one of the three big clubs in terms of the number of paying fans. (Grow, 1998, p. 55) The South Melbourne Football Club, that eventually became the Sydney Swans, began with most of their supporters being aspirational members of the lower-middle-class. (Shaw, 2006, p. 116) During the 1930s, the club was considered a Catholic one. (Shaw, 2006, p. 116) During 2009, the club ranked first in the AFL with 1,217,000 fans. (Roy Morgan Research, 2009, July 19)

During the 1880s, St. Kilda fans were characterized as being stockbrokers. (Grow, 1998, p. 69) The 2009 team ranked twelth for total fans, with 311,000 fans. (Roy Morgan Research, 2009, July 19).

Demonstrating Club Allegiance

In the AFL, fans has historically expressed their allegiance to their clubs in a variety of ways.

Up until about thirty years ago, if the Collingwood Magpies performed poorly, The Sporting Globe no one would buy it. (Shaw, 2006, p. 117)

The morale of the city of Geelong is said to be dependent on the club’s performance. (Shaw, 2006, p. 116)

During the 1920s, the North Melbourne Kangaroos were called “The Shinboners” because, according to Shaw (2006, p. 83), many fans from the area the team drew from were butchers and “would attach royal blue ribbons to animals’ shinbones and use them as window displays before North Melbourne home games.” (Shaw, 2006, p. 83)

The Connection Between Sport Fandom and Online Activity

References

Adair, D. & Vamplew, W. (1997). Sport in Australian History. Melbourne: Oxford University Press.

Cashman, R. (2002). Sport in the National Imagination, Australian sport in the Federation decades. Sydney: Walla Walla Press.

Collins, T. (2005). “‘One Common Code of Football for Australia!’: The Australian Rules and Rugby League Merger Proposal of 1933.” In R. Hess, M. Nicholson, & B. Stewart (Eds.), Football Fever: Crossing Boundaries (pp. 27-38). Hawthorn: Maribyrnong Press.

Depley, L. and Boetti, H.A. (1998). “Sport Management and Marketing via the World Wide Web”, Sport Marketing Quarterly, 7 (1), pp. 21-27.

Grow, R. (1998). The Victorian Football Association in Control, 1877-1896. In R. Hess & B. Stewart (Eds.), More Than a Game (pp. 45-85). Melbourne: Melbourne University Press.

Jenkins, H. (2006) Convergence Culture: Where Old and New Media Collide. New York: New York University Press.

Nicholson, M. (2004). “Take the Game to the North: The Strategic and Demographic Imperative Facing Australian Rules Football.” In M. Nicholson, R. Hess, & B. Stewart (Eds.), Football Fever: Grassroots (pp. 111-121). Hawthorn: Maribyrnong Press.

Roy Morgan Research. (2009, July 19). More Than 7.6 Million AFL Supporters A Great Market for Prospective Sponsors 2008 Grand Finalists Hawthorn (Up 72,000) & Geelong (Up 99,000) Have Biggest Jumps in Support. [Press Release]. Retrieved from http://www.roymorgan.com/news/press-releases/2009/906/

Sandercock, L., & Turner, I. (1981). Up Where, Cazaly? The Great Australian Game. Sydney: Granada.

Shaw, I. W. (2006). The Bloodbath, The 1945 VFL Grand Final. Melbourne: Scribe.

Shilbury, D., Quick, S., & Westerbeck, H. (2003). Strategic sport marketing (2nd ed.). Crows Nest, New South Wales: Allen & Unwin.

Smith, A. and Stewart, B. (1999) Sports Management: A Guide to Professional Practice, Allen & Unwin, Sydney.

Stewart, B. (1983). The Australian Football Business, a Spectator’s Guide to the VFL. Maryborough, Victoria: Kangaroo Press.

Sullivan, M. (2004). “Sports Marketing.” In J. Beech & S. Chadwick (Eds.), The Business of Sport Management (pp. 128-153). Essex: Pearson Education Limited.

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I’ve wanted to compare the NRL to the AFL on Twitter for a long time.  The problem is that they have a lot of followers.  For other teams, based on where our API is right now, there might be 200 to 300 location fields not filled in.  In both cases, there are were 6,000+ total followers.  Despite having massively improved the tool we’re building,  we’re still missing a lot.  In terms of the NRL data we gathered on September 2, we’re missing 836 locations.  (These may or may not actually result in actual city, state, country locations.)   For the AFL data gathered on the same date, we’re missing 351 locations.  At this would require several more days worth of work to fix, I figured there was enough data to draw some general conclusions and make a map of the comparative locations of AFL fans versus NRL fans.

For the AFL, the city was determined for 5,879 people who are from 891 unique cities.  For the NRL, the city was determined for 3,204 people who are from 493 unique cities.  The following table shows the follow count by city and league for all cities+leagues where the city had more than 100 people identified as from that location.

The location follow patterns appear to makes sense given what are the traditional strongholds and relative popularity of each league.  (It would be interesting to compare these to the A-League, ANZ Championship, W-League, NBL, WNBL, Super 14/15 and national side related follows to see where cities rank.  That map is a project for another day.)  When mapped with the location by city+league followed, you get the following:

View full map

The map shows that the NRL draws much more heavily in New Zealand than the AFL does. Victoria, Western Australia, Tasmania and South Australia are predominately AFL areas of followers; whereas, New South Wales and Queensland are areas of heavy followers for the NRL.

If the location data is broken down by state instead of city, 3,546 NRL and 6,681 AFL followers have an identifiable Australia state. It reaffirms the observed patterns:

Both teams appear to have strong follower populations international.  For the NRL, 4,987 followers have an identified country.  For the AFL, there are 8,671 who have an identified country.  With the exception of Uruguay, New Zealand and the United Kingdom, the AFL has the largest amount of followers by country.

With out knowing much, some of this makes sense.  It is much easier to watch AFL games in the United States and Canada than it is to watch NRL games.  Added to that, the AFL have spent some money trying to develop the sport there.  The United Kingdom is a traditional rugby stronghold.  New Zealand has an NRL team and doesn’t have an AFL club.

On September 2, I also got follower data for the Socceroos and the ANZ Championship.  The scale of followers was much smaller, with something like 4,500 and 250 respectively.  For the accounts, I found the mean, median and mode of ReTweets, Followers, Status Updates, Friends, and Listed.  This data is on the table below.

On the whole, Socceroos fans appear to be more active, have the most followers and follow the most people.  If we only look at the NRL and the AFL, the two sets of followers appear to be very close in composition.  The average number of followers is separated by one. The total status updates differs by a little more than 10.  The total number of friends differs by around 9.  The total number of times each follower appears on a list averages less than one.  If median and mode are used instead, the differences are similar in that there isn’t a significant difference.

In conclusion, there are distinct geographic patterns for AFL and NRL followers but beyond that, the two types of followers are pretty similar.  More analysis can and should be done to see if these patterns hold up country to country, state to state, and city to city.

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When I say part 4, what I mean is that this this includes everything you’ve seen in earlier parts… and I’ve just added bits here and there. In this case, I’ve added about 800 words. I’ve managed to complete about seven of the ten sections of my methodology so far. Even though seven sections are done, this is still very much a draft as the grammar has issues, there are organizational issues, there may be incomplete thoughts, etc. A lot of this blog is about showing other people the process of writing a dissertation. As I’m writing about social media and social media moves so fast… posting this in this format feels appropriate. Onwards with my latest…

Methodology

When conducting social media research, there are ten general methods that can be used to gather and analyze data. These are:

1. Individual case studies for how a business uses social media and the web;
2. Search and traffic analytics analysis;
3. Sentiment analysis and reputation management;
4. Content analysis;
5. Usability studies;
6. Interaction and collaboration analysis;
7. Relationship analysis to try to determine how people interact and to identify key influencers;
8. Population/demographic studies;
9. Online target analysis of behavior and psychographics; and
10. Predictive analysis.

Each of these methods offers insights into various aspects of the web and its population. The type of analysis used is often specific to the purpose of the research, involved blended approaches from traditional analysis types, and different methods are often used in conjunction with each other. These methods often blend quantitative and qualitative analysis. Choosing the correct method of gathering analyzing data can be one of the biggest hurdles for being able to measure ROI and understand how a community works.

This section will provide a brief summary of each type, explain how to conduct this type of research and give examples that used that methodology.

Individual case studies for how a business uses social media and the web (COMPLETE)

Case studies on social media usage are often done to measure the effectiveness of specific actions taken by an organization.

Bronwyn et al. (2005) say case studies “typically examine the interplay of all variables in order to provide as complete an understanding of an event or situation as possible. This type of comprehensive understanding is arrived at through a process known as thick description, which involves an in-depth description of the entity being evaluated, the circumstances under which it is used, the characteristics of the people involved in it, and the nature of the community in which it is located.”

This methodology often incorporates components of all the other methods discussed in this section. The specific methods often depend on the goals of the person or organization conducting the case study.

Vincenzini (2010) did a case study regarding the use of the social media by the NBA in an attempt to define why they have been successful in using it to promote the league. The author used quantitative analysis to measure the size of the community, the volume of content they were viewing on sites like YouTube and the volume of content they were creating on sites like Twitter. The quantitative analysis was synthesized with explanations from NBA employees to explain their practices in the context of their own business decisions as they pertained to social media. This was followed up with an explanation as to what worked and what did not worked and offered advise for others involved with sport and social media to help them leverage their own position.

Case studies are a mixed methodology approach, borrowing from other approaches. The major difference is that the case study focuses on a narrower perspective with the goal of tracking behavioral changes, or in advising others on how an organization changed practices and how those lessons can be applied elsewhere.

Search and traffic analytics analysis (COMPLETE)

Search engine and traffic analytics generally is done internally to determine how to optimize a site in order to increase the amount of visitors a site gets and the total number of pages that they view. This method involves identifying how people arrive at a specific site and the pages they visit while at the site. Traffic analytics analysis often includes six different components: Search engine visitors, paid search advertisements, pay per click, organic traffic, direct traffic and internal site traffic.

Ramos and Cota (2009) define traffic analytics as “Tools that analyze and compare customer activity in order to make business decisions and increase sales. Analytics tools can report the number of conversions, the keywords that brought conversions, the sites that sent converting traffic, conversion by campaign, and so on.”

There are a number of different methods and tools that allow for this type of analysis. Early in the history of the Internet, one of the most popular tools and methods involved analyzing web server log files. (Jansen 2009) Another popular early method of analysis was page tagging, which involved embedding an invisible image on a page, which, when the image is triggered, “triggers JavaScript to send information about the page and the user back to a remote server.” (Jansen 2009) These earlier tools have advanced a bit and now include tools like Quantcast and Google Analytics. Kaushik (2010) recommends Google Analytics, a free tool that involves putting a bit of code on all pages of a site. Kaushik (2010) points out that various types of traffic analysis can be done using the various tools provided by Google Analytics. The author claims that Google Analytics allows you to break the analysis down into “three important pieces: campaign response, website behavior, and business outcomes.” (Kaushik 2010)

Fang (2007) completed a case study at the Rutgers-Newark Law Library in order to track library website usage, track visitor behavior and determine how to improve the website to better serve users. Earlier work done by the library had involved surveys handed out to patrons, analysis of log files, and the use of counters. (Fang 2007) The author changed methods because of some inherent flaws in using those methods to analyze website needs. They used Google Analytics in order to track user activity on the library’s website. The library “found out how many users were accurately following the path we had designed to reach a target page.” (Fang 2007) This sort of path following navigation was one of the goals they had when they designed their site. They also found out that “Visitor Segmentation showed that 83% of visitors were coming from the United States. About 50% of U.S. visitors were from New Jersey, and 76% of these were from Belleville and Newark. These results matched our predictions for patrons’ geographical patterns.” (Fang 2007) The results of this analysis enabled the library to make changes to improve their website.

This type of methodology lends itself more to a case study approach and often requires the consent of the website involved in order to get private logs. It can be used in conjunction with other methods, but should be used in a more targeted analysis of highly specific research areas.

Sentiment analysis and reputation management (COMPLETE)

Sentiment analysis involves identifying content related to a topic and identifying the emotion connected to that content. In a sport context, sentiment analysis could involve determining if newspapers are providing positive or negative coverage of a team. In a social media context, sentiment analysis would involve determining attitudes being expressed on Twitter in individual tweets. Reputation management goes one further: After sentiment has been determined, a decision needs to be made on if and how negative and positive sentiment content should be responded to. Sentiment analysis is passive analysis where non-stakeholders can conduct analysis. Reputation management is active analysis that is primarily conducted by stakeholders as part of on going activities to improve a brand, be it personal or corporate.

While sentiment analysis and reputation management are similar in their desire to monitor a response to a situation, the tools available vary differently for each type. There a variety of different tools for sentiment analysis. One of the tools for conducting sentiment analysis are freely available lists of words “that evoke positive or negative associations.” (Wanner et al. 2009) Sterne (2010) suggests that content being ReTweeted on Twitter can be seen as a tool to measure positive sentiment. Sterne (2010) suggests that the ratio of follows/followers is not an effective tool for measuring sentiment on Twitter. Reputation management tools include Trackur. It allows you to “set up searchers and the system automatically monitors the Web for key words that appear on news sites, blogs, and other social media.” (Weber 2009)

Wanner et al. (2009) did a sentiment analysis of RSS feeds that focused on the 2008 United States presidential elections. They selected 50 feeds connected to the elections and collected updates to these feeds every 30 minutes for one-month starting 9 October 2008. For each item they collected off the feeds, they also recorded the date, title, description and feed id. (Wanner et al. 2009) After that, they eliminated all noise, which mostly consisted of non-content like URLS. (Wanner et al. 2009) The next step was to filter out all items that did not contain one of the following terms: “Obama”, “McCain”, “Biden”, “Palin”, “Democrat” and “Republican”. (Wanner et al. 2009) Sentiment was then analyzed using freely available lists “that evoke positive or negative associations.” (Wanner et al. 2009) The results were then visualized. Five events that happened during this period were chosen for a more detailed visual examination. They found that the news regarding possible abuse of power by Sarah Palin in Alaska resulted in many negative posts. They also found that the debates resulted in low sentiment scores for both candidates as the candidates attacked each other. The authors concluded that the visual tool they created would be useful for monitoring public debates.

This methodology can overlap with influencer identification (Weber 2009) as part of reputation management involves determining which people are worth responding to. It can also overlap with psychographics. Despite the obvious overlaps, this type of research often appears independently and not as part of a larger study.

Content analysis,

Content analysis involves looking at the individual components of something larger and analyzing it. In a social media context, the content could be comments on a Facebook fanpage, or all the tweets made by a person or group.

With content analysis, the researcher views data as “data as representation not of physical events but of texts, images and expressions that are created to be seen, read, interpreted, and acted on for their meanings, and therefore be analyzed with such uses in mind.” (Krippendorff 2007) Krippendorff (2007) defines the basic methodology used in content analysis as unitizing, sampling, recording, reducing, inferring, and narrating.

Usability studies,

According to Sweeney, Dorey and MacLellan (2006), one of the purposes of a usability study is “point out specific usability problems with your Web site interface in line with how well your Web site speaks to your audience and their goals.”

Usability studies can be done in conjunction with traffic analysis and search analytics as the purposes are often similar: Improve the user experience and try to get users to complete certain tasks.

Interaction and collaboration analysis,

Viégas et al. (2007) did a collaboration analysis focusing on Wikipedia. The purpose of their work was to examine historical editing patterns and how editing practices have evolved over time. They built on work done by Viégas, Wattenberg and Dave in 2003. The methodology they used involved getting the editing history of articles across several different Wikipedia namespaces. The history of the articles was then examined using several visualization tools, metrics and methods depending on the established cultural practices for that namespace. One tool they used was a history flow visualization application. A method they used was the manual classification of “all user posts in a purposeful sample”. (Viégas et al., 2007) Metrics they used included count of horizontal rules, signed user names, new indentations levels, votes in polls and total “references to internal Wikipedia resources.” (Viégas et al., 2007) These tools, metrics and methods allowed them to examine how collaboration and interaction had changed over time.

Relationship analysis (COMPLETE)

Relationship analysis involves examining the relationships between users on a social network, message board or mailing list. The goal is to identify cliques of different sizes or people who are particularly influential in a particular group online. This type of analysis is important to many brands including Starbucks (Plimsoll, 2010). The purpose of relationship analysis is to identify key influencers and social who influencers who are or who have the potential to be brand evangelists. (Plimsoll, 2010)

Lord and Singh (2010) define social media influence marketing as being “about recognizing, accounting and tapping into the fact that as your potential consumer makes a purchasing decision, he or she is being influenced by different circles of people through conversations with them, both online and off.”

The methodology for influence identification is not clearly spelled out as identifying influencers can be heavily dependent on the network being examined and how the community on a specific site functions. As a result, social media marketers suggest an array of tools like Twitalyzer that can be used to help determine your own influence. (Ankeny 2009) Twitalyzer’s Peterson and Katz (2010) explain their site-specific method of determining influence as including the following variables: Engagement level, total followers, total following, hashtags cited, lists included on, frequency of updates, references by others, references of others, times content is retweeted, urls cited and a number of other variables. Sterne (2010) suggests using WeFollow.com to find people who use topic specific #hashtags on Twitter. The people who tweet the most about a topic are likely to be influencers in that others looking for tweets around a topic are likely to read them. In a wider web context, Sterne (2010) suggests using Technorati to identify bloggers who have clout and influence around a certain topic.

This type of research can be viewed as a fundamental component to sentiment analysis; social media marketing companies like Razorfish often package the two together. (Lord & Singh, 2010)

Population /Demographic studies (COMPLETE)

Population studies involve defining the demographic characteristics of a community. In a population study, the goal is also to define the limits and size of the community that is being studied. Because of the complexity in defining the boundaries of a population and in sampling the whole of it, this type of research is rarely done in terms of social media.

Daugherty and Kammeyer (1995) define a population study as the assembling “of numerical data on the sizes of populations.” This sort of data is defined by the authors as “descriptive demographic statistics.” Daugherty and Kammeyer (1995) say “population numbers are always changing, so even if they are accurate when gathered they are soon out of date and inaccurate.” Daugherty and Kammeyer (1995) say the basic purpose of conducting a demographic study “is to explain or predict changes or variations in the population variables or characteristics.” Given the definition of a population study, the methodology involves counting all members of a select population.

The most famous example of a population study is the census. In the United States, this is done every ten years. According to the U.S. Census Bureau (n.d), the goal of the 2010 US census is ” to count all U.S. residents—citizens and non-citizens alike.” This is done by sending all citizens a ten-question questionnaire, requiring that people complete it by law and having a census taker follow up for all households did not return completed questionnaires. (U.S. Census Bureau, n.d.) The results are then calculated and are used by the government to make decisions.

This type of research often stands on its own. The results will often be utilized for marketing purposes in conducting other research, such as psychographics, to make that that sampling contains representative populations.

Online target analysis of behavior and psychographics (COMPLETE)

Online targeting of and marketing towards a specific audience because of their demographic characteristics is extremely common on the Internet. Psychographics is a term that includes targeting towards a specific demographic group except it includes the offline component.

Sutherland and Canwell (2004) define psychographics as “market research and market segmentation technique used to measure lifestyles and to develop lifestyle classifications.” (p. 247) Nicolas (2009) defines online behaviorial analysis as a series of steps: Collecting user data across several sites, organizing information about users based on the sites they visit and their behavior on those sites, “infer demographics and interest data”, and classifying new users based on the collected data in order to deliver relevant ads and content based their demographic profiles. Kinney, McDaniel, and DeGaris (2008) define psychographics as attitude towards something such as a brand or involvement with an organization.

Given the methodology involved, much of this type of research involves action research in that it is done in a specific content, based on internal models to address specific situations.

An example of this type of research was done by Kinney, McDaniel, and DeGaris (2008) who investigated the demographic characteristics of NASCAR fans and their attitudes towards NASCAR, its sponsors and sponsor involvement with NASCAR. The research found that age, gender and education were all important variables in determining sponsor recall: Younger, more educated males had the best brand recall amongst NASCAR fans.

This type of research can be viewed as a subcomponent of a population study in that demographic information is sought about the population. In an online context, it often works in conjunction with search and traffic analytics analysis, content analysis, and interaction and collaboration analysis.

Predictive analysis (COMPLETE)

A search on 13 July 2010 on SPORTDiscus had three results for “predictive analysis.” A search on the same date on Scopus had 605 results, 275 of which were in engineering, 132 in computer science and 102 in medicine. Predictive analysis is probably one of the least used analysis methods, especially in social media and fandom.

What is predictive analysis? At its simplest, it is identifying a future event or events, monitoring selection actions that precede the event and seeing if those events can be used to predict the outcome of similar events in the future. If a predictive value is found, an organization can monitor behaviors to help make more informed decisions.

An example of this type of research is “Predicting the Future With Social Media” by Asur and Huberman (2010). Their goal was to determine if tweet volume and sentiment on Twitter prior to a movie being released could be used to predict how well a movie performs at the box office. Their methodology involved identifying movie wider release dates that took place on a Friday, creating a list of keyword searches related to those movies, and using the Twitter API to collect all tweets and aggregate date that mention those keywords over a three month time period. The authors then compared the tweet volume to box office performance. They concluded that social media “can be used to build a powerful model for predicting movie box-office revenue.” (Asur & Huberman, 2010)

This type of research can be used in conjunction with other methods. It can be used along side a population study to see if certain actions will result in demographic changes.
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