Social Sochi: Using Social Network Analysis to Investigate Electronic Word-of-Mouth Transmitted...

120 Int. J. Sport Management and Marketing, Vol. 15, Nos. 3/4, 2014

Copyright © 2014 Inderscience Enterprises Ltd.

Social Sochi: using social network analysis to investigate electronic word-of-mouth transmitted through social media communities

Marion E. Hambrick* Department of Health and Sport Sciences, University of Louisville, HP/Studio Arts Room 104 Louisville, KY 40292, USA Fax: +1-502-852-8286 Email: [email protected] *Corresponding author

Ann Pegoraro Faculty of Management, School of Sports Administration, Laurentian University, 935 Ramsey Lake Road, Sudbury ON P3E 2S2, Canada Email: [email protected]

Abstract: The 2012 London Summer Games earned the nickname ‘the Twitter Olympics’ for the social media coverage of the mega-event (Whiteside, 2014), and the 2014 Sochi Winter Games witnessed a marked increase in this activity. This study examined social media communities formed during the 2014 Olympic Games. Employing the word-of-mouth (WOM) conceptual framework and social network analysis (SNA), the study examined three social media communities within Twitter – #WeAreWinter, #CheersToSochiand #SochiProblems – and messages posted from February 7–25, 2014, incorporating one of the three hash tags. The findings revealed communities first characterised by spikes in growth often coinciding with viral posts, and later by eventual network decay as the Olympic Games concluded. The most viral messages contained either celebratory information or satirical content. Additionally, key users emerged in each community, most frequently individuals rather than corporate entities and media outlets. Theoretical and practical implications will be discussed.

Keywords: social network analysis; SNA; Olympic Games; word-of-mouth; WOM; hash tags; Twitter.

Reference to this paper should be made as follows: Hambrick, M.E. and Pegoraro, A. (2014) ‘Social Sochi: using social network analysis to investigate electronic word-of-mouth transmitted through social media communities’, Int. J. Sport Management and Marketing, Vol. 15, Nos. 3/4, pp.120–140.

Biographical notes: Marion E. Hambrick is an Assistant Professor at the University of Louisville in the Department of Health and Sport Sciences. His research interests include social media usage in sport and recreational sport participation.

Social Sochi: using social network analysis 121

Ann Pegoraro is the Director of the Institute for Sport Marketing (ISM) and holds an appointment as an Associate Professor in School of Sports Administration, all at Laurentian University. She has published in the areas of sport management, marketing, social media and communications. Her research primarily focuses on the intersection of sport and new media, particularly social media. Her work has been published in the International Journal of Sport Communication, Communication and Sport, American Behavioral Scientist, Journal of Sport Management, the International Journal of Sport Marketing and Management and the Journal of Sponsorship.

1 Introduction

Social media users sent a record number of Twitter messages, or tweets, during the London 2012 Summer Olympic Games, also known as the ‘Twitter Olympics’. The 2014 Sochi Winter Olympic Games built upon this social media activity, and event organisers, sponsors, athletes and viewers used Twitter and other social media platforms to discuss and promote the games. This increased activity led one industry analyst to assert, “social media [] changed the way the Olympics are consumed and discussed” [Whiteside, (2014), para. 5].

Social networks (SNS) such as Facebook and Twitter allow users to develop spontaneous and global communities around a particular activity or event. In the case of the Sochi Winter Olympic Games, the local organising committee used these platforms to publicise the event in the months, weeks and days leading up to the opening ceremonies. Similarly, sponsors broadcast their affiliation with and support of the Olympic Games, while athletes, journalists and others in attendance provided a first-hand account and discussed related topics and issues via the same platforms. Those watching in the stands and at home also took part in the conversation as they witnessed the athletic performances unfold through social media and other communications channels. Through these activities, impromptu or ad hoc sports communities developed around the Olympic Games and gave users an opportunity to participate in the ever-evolving conversations circling these proceedings (Whiteside, 2014).

Social media can play an integral role in the sporting event experience to varying degrees and with varying effects, whether to highlight positive occurrences such as supporting athletes or to expose negative topics and issues. Researchers can explore these social media activities via social network analysis (SNA), which suggests individuals and groups form relationships, and the combination of individuals, groups and their accompanying relationships form networks used to exchange information and other resources (Laumann et al., 1978). Social networks can develop offline with sports facilities (MacLean et al., 2011) and teams (Warner et al., 2012). They also can occur in online settings, as SNS facilitate the creation of these networks (Bruns and Burgess, 2011). SNA can help event organisers understand how social media communities develop and expand their knowledge of how these communities can play a critical role in the conversations occurring around their events-whether through positive or negative word-of-mouth (WOM) (Sahelices-Pinto and Rodríguez-Santos, 2014). Limited research has explored the connection between sport-related social media usage and social networks via SNA (Clavio et al., 2012; Hambrick, 2012; Hambrick and Sanderson,

122 M.E. Hambrick and A. Pegoraro

2013). The current study examined how users formed social media communities to discuss the Sochi 2014 Winter Olympic Games.

2 WOM communication

The internet, and Web 2.0, in particular, has changed how society functions. As part of their everyday lives, individuals send emails, write or comment on blogs and participate in forums, websites and social media platforms. A large portion of communications previously characterised as face-to-face has moved online, resulting in an unprecedented amount of consumer-generated information that impacts all aspects of decision-making, including those decisions surrounding the purchase and use of goods and services (Goldsmith and Horowitz, 2006). This consumer-generated information is labelled WOM communication, which “refers to informal communication between two people about positive and negative experiences related to products, services, brands or companies” [Sahelices-Pinto and Rodríguez-Santos, (2014), p.245].

In the marketing literature, Arndt (1967) pioneered WOM communication research; he recognised this importance of WOM and studied the effects of positive WOM (PWOM) and negative WOM (NWOM). He determined that PWOM occurs more frequently than NWOM, and consumers received favourable WOM eight times more often than unfavourable WOM (Arndt, 1967). More recently, East et al. (2008) found that consumers received PWOM three times more frequently than NWOM across several categories. The authors also noted that generally PWOM has more of an impact than NWOM, whereas others have claimed that NWOM can be more influential (Bayus, 1985).

This body of research has become significant in marketing, as researchers try to understand the capacity of WOM to influence and to determine consumer attitude and behaviour with respect to a product, service, brand or company (Brown and Reingen, 1987; Christiansen and Tax, 2000; Nadeem et al., 2011). The capacity of WOM to influence consumers can greatly impact the marketplace. WOM can simultaneously raise awareness on a cognitive and emotional level about a brand, and ascribe a feeling, sense or meaning to that brand, while at the same time on a co-native and behavioural level, WOM can stimulate a response to either purchase or reject that brand (Sahelices-Pinto and Rodríguez-Santos, 2014).

These WOM communications, whether positive or negative, can occur in offline and online settings. Online WOM, including in the realm of SNS with Facebook and Twitter, is labelled as electronic WOM or eWOM, and researchers have recognised the importance of these online conversations to brands (Armstrong and Hagel, 2000; Sahelices-Pinto and Rodríguez-Santos, 2014). Information pertaining to companies and brands flows freer and faster in eWOM than in traditional WOM due to two main differences (Sahelices-Pinto and Rodríguez-Santos, 2014). First, local boundaries do not constrain this information; consumers can connect with other consumers beyond their personal circle, which usually includes relatives, friends and acquaintances. Second, eWOM in SNS also crosses geographical and socio-cultural boundaries, allowing consumers to connect with other consumers they do not and probably never will know, but with whom they share a common interest (Sahelices-Pinto and Rodríguez-Santos, 2014). As a result, marketers have become more aware of the possibility that online


discussions can, and do, impact sales, reputations and brands. EWOM can create marketing opportunities and just as easily result in online crises. It occupies a central place in the consumer decision process, and has become an important part of consumer behaviour (Ganim Barnes and Jacobsen, 2014).

This study will examine how social networks within online environments can spur eWOM, focusing more specifically on social media communities initiated during the 2014 Sochi Winter Olympic Games and how users within these communities connected with one another and engaged in eWOM throughout the mega-event. Previous sports-related work in this area has concentrated on Twitter and the development of eWOM communities discussing sports organisations such as university athletic departments (Brown and Billings, 2013; Clavio et al., 2012; Hambrick and Sanderson, 2013) and event organisers (Hambrick, 2012) as well as major sporting events such as the 2011 Major League Baseball World Series (Blaszka et al., 2012), 2012 London Summer Olympic Games (Frederick et al., 2013; O’Hallarn and Shapiro, 2014), and 2012 College World Series (Smith and Smith, 2012).

These studies documented users coming together and sharing their sentiments or promoting specific messages and products. In most instances, individuals offered their thoughts and feelings about various topics or as they watched sporting events. Their messages featured eWOM perceived as positive (Brown and Billings, 2013), negative (O’Hallarn and Shapiro, 2014) and mixed (Smith and Smith, 2012). The authors noted these messages could influence how others viewed certain issues or made decisions about products. As social media activities continue to grow, sports organisations could benefit from understanding how social media communities develop and how to effectively use eWOM to manage these conversations and market their products.

2.1 Social media communities and SNA

EWOM opportunities can develop within SNS, and create marketing advantages and disadvantages as users share information. Although marketers expressed interest in social networks for WOM marketing, they previously ignored the importance of understanding network structures (Van den Bulte and Wuyts, 2007). Marketers have focused on the role of opinion leadership and contagion processes in new product diffusion and adoption when executing marketing strategies while overlooking the structures of social networks (Van den Bulte and Wuyts, 2007). Recent research in social networks and WOM has challenged the commonly accepted notion that WOM influence comes from an elite, highly-connected few known as opinion leaders (Smith et al., 2007). Instead, moderately connected individuals prove just as willing to share marketing messages. When taking these new findings into consideration, then it becomes necessary to understand the social network structure and the relationship strengths between members as almost every individual within the network could potentially spread marketing messages (Wang et al., 2013).

Within the Twitter environment, researchers have explored these social networks and the stature of various users in more detail, and Bruns and Burgess (2011) argued the networks and their accompany activities could be examined via SNA. Social media communities represent a social network, defined as “a set of nodes (e.g., persons, organisations) linked by a set of social relationships (e.g., friendship, overlapping membership) of a specified type” [Laumann et al., (1978), p.458]. Researchers have used


SNA as a methodological approach to examine a variety of contexts and the viral nature of information spread through them. They have applied SNA often outside of sports to explore social media platforms and the resulting communities formed within them (Bruns and Burgess, 2011).

A more limited number of studies have employed SNA within sports in offline settings (MacLean et al., 2011; Warner et al., 2012). This study will use SNA to explore the online setting of the 2014 Winter Olympic Games social media communities and eWOM conversations taking place within them. Previous sports-related research has used SNA to examine the development of social networks and the eWOM information exchange, and concentrated primarily on exchanges within the Twitter environment (Clavio et al., 2012; Hambrick, 2012; Hambrick and Sanderson, 2013). Their findings noted the speed at which information moves through Twitter can grow and subside at exponential rates, and these dissemination efforts can help organisations reach a larger number of users within their respective social media communities (Hambrick, 2012; Hambrick and Sanderson, 2013). Additionally, certain individuals or groups can operate as primary information sources and hubs, and may control the development and distribution of news and other resources. Sports organisations and events can benefit from popular social media users and groups who spread positive news and information to other users (Clavio et al., 2012; Hambrick and Sanderson, 2013).

2.2 Research purpose and questions

As noted above, SNA has seen limited use within sports, where researchers have employed the methodological tool to investigate sports organisations (MacLean et al., 2011; Warner et al., 2012) and social media users (Clavio et al., 2012; Hambrick, 2012; Hambrick and Sanderson, 2013). Therefore, this study examined social media communities forming during the 2014 Sochi Winter Olympic Games and the use of eWOM during this mega-event. The study addressed two research questions:

RQ1 What social media communities formed during the 2014 Winter Olympic Games?

RQ2 What similarities and differences emerged among the social media communities?

3 Method

3.1 Social network analysis

This study extended the sports-related SNA social media research by focusing on eWOM and social media communities formed during the 2014 Sochi Winter Olympic Games. These communities can develop through Twitter and a hash tag “used to mark keywords or topics in a tweet. It was created organically by Twitter users as a way to categorise messages” [Twitter, (2014), para. 1]. More sports organisations and events use social media marketing campaigns and hash tags to initiate and sustain discussions around their products (Whiteside, 2014). Event organisers and sponsors can strategically introduce them in conjunction with the event’s start, while others may emerge more organically. This study examined social media communities occurring around three types of hash tags:


a marketing – #WeAreWinter

b hijacked – #CheersToSochi

c organic – #SochiProblems.

3.1.1 Marketing

Sports organisations and others can use eWOM to promote their goods, services, companies and brands (Sahelices-Pinto and Rodríguez-Santos, 2014). Within Twitter, these promotional activities can take the form of official marketing hash tags created by specific organisations. The Canadian Olympic Committee used #WeAreWinter to support its athletes and their performances (Brown, 2013), and this hash tag reflected the marketing purposes of the organisers as they promoted the country and its athletes on an international stage.

3.1.2 Hijacked

While some online marketing campaigns offer PWOM, others can create negative effects. Despite their best efforts, hash tag creators may face the risk of ‘hash tag hijacking’, which occurs when a different individual or group uses the hash tag in opposition to the creator’s original intent (Elliott, 2014). McDonalds developed #CheersToSochi to promote athletes and its sponsorship of the Winter Olympic Games. Lesbian, gay, bisexual, and transsexual (LGBT) activists appropriated the hash tag almost immediately, and used it to deride Russian President Vladimir Putin and anti-gay discriminatory practices in Russia (Moores, 2014).

3.1.3 Organic

In contrast to strategically developed marketing hash tags, organic hash tags can emerge as Twitter users spontaneously coalesce to discuss a topic or event. The #SochiProblems hash tag appeared alongside official ones to highlight various issues, particularly those related to accommodations for Olympic athletes and journalists (Whiteside, 2014).

Twitter users created and used the three hash tags for varying purposes. Examining their similarities and differences would provide insights into the following:

a How users employ eWOM to create an official marketing hash tag as originally designed to offer PWOM.

b How users spur and respond to marketing hash tag hijacking and NWOM.

c How users create an organic eWOM hash tag and how this hash tag could have an impact on the nation hosting the Olympic Games, whether positively or negatively.

The study used SNA to examine these three social media communities – #WeAreWinter, #CheersToSochi and #SochiProblems – in more detail. The information facilitated the study of communities emerging from this hash tag usage, and helped to identify potentially influential or key Twitter users within each social media community. SNA socio-grams provide a visual representation of a social network. Graphically, circles depict the network’s members, and lines connecting the circles reflect the shared relationships among them. The collection of members and relationships represents the


social network. Within a social media community occurring around a hash tag, socio-grams reflect the exchange of tweets among hash tag users, as they create an environment to discuss a particular issue or event.

3.2 Data collection

This study examined the three 2014 Winter Olympic Games hash tag and their usage from February 7–25, 2014, and assessed how the social media communities developed plus potential similarities and differences among the communities. The first step in this process involved hash tracking, a commercial tracking software system that researchers have utilised in previous studies to investigate the use of Twitter during national elections (Kalsnes et al., 2014) as well as to monitor Twitter eWOM around movies (Deltell et al., 2013) and the future of higher education (Conway, 2012). The researchers entered the three hash tag into the hash tracking tool, and collected data for each hash tag for the entire period of the 2014 Winter Olympic Games.

The collected data included the following:

a total number of tweets containing each hash tag

b contributors – the number of users including the hash tag in their tweets

c timeline deliveries – the total possible number of times someone could view a message based on the original tweeter’s followers and the followers of any re-tweeters

d reach – the number of unique individuals who received timeline deliveries of hash tag messages.

Because the same user could receive multiple timeline deliveries, measuring reach as well as deliveries allowed for a better understanding of the true spread of any message. Table 1 Social media community data for the 2014 Winter Olympic Games time period

Social media community

Total no. of tweets Contributors1 Average tweets/

contributor Timeline

deliveries2 Reach3

#WeAreWinter 1,043,755 318,822 3.27 1,403,164,510 208,551,695 #CheersToSochi 26,399 7,989 3.30 46,167,617 17,234,784 #SochiProblems 435,355 292,205 1.49 1,142,933,502 416,672,919

Notes: 1Contributors are all the people who tweet with a particular hash tag. Everyone who tweets or re-tweets a message with this hash tag is counted as a contributor. 2Timeline deliveries represent the total possible number of times someone could have viewed a particular message. The follower count of the original tweeter is used and the followers of any re-tweeters are added to generate the total number of timeline deliveries for each and every hash tagged tweet. 3Reachreflects the number of unique individuals who received timeline deliveries of hash tagged messages. Because the same users may receive multiple timeline deliveries, measuring reach as well as deliveries allows for a better understanding of the true spread of any message.

This information would provide insights into the relative usage and popularity of the hash tag as Twitter users discussed the Olympic Games. In total, the #WeAreWinter hash tag amassed 1,043,755 tweets written by 318,822 contributors. The number of timeline


deliveries equalled 1,403,164,510 with a reach of 208,551,695. The #CheersToSochi hash tag accrued 26,399 tweets written by 7,989 contributors. The number of timeline deliveries equalled 46,167,617 with a reach of 17,234,784. Finally, the #SochiProblems hash tag attained 435,355 tweets written by 282,205 contributors. The number of timeline deliveries for these collected tweets equalled 1,142,933,502 with a reach of 416,672,919 (Table 1).

Next, the researchers used NodeXL, a free and open source software add-in to Excel, to collect data from Twitter for the three hash tag. NodeXL allows users to explore social media communities via SNA by downloading data from Twitter and other platforms (Himelboim et al., 2013). For the purpose of this study, the researchers collected data using each specific hash tag (#WeAreWinter, #CheersToSochi, #SochiProblems) through NodeXL and requested a minimum of the most recent 5,000 tweets posted daily. Twitter sets limits on the number of tweets collected each day, and this can range from a few hundred tweets to the full amount requested, depending on Twitter traffic and throttling mechanisms put into place by the social media platform. Thus, the data collected and examined for this study do not represent the full set of tweets distributed during the Olympic Games, but rather a subset based on the selected hash tag and NodeXL’s daily collection capacity within the specified time period of February 7–25, 2014.

The data collected included the tweets incorporating each hash tag as well as the self-descriptions and statistics for each hash tag user such as total number of tweets posted, date the user joined Twitter and total number of followers. The researchers collected data each day during the 19-day period around the 2014 Winter Olympic Games, and encompassed the entire Games timeframe plus a few days before and after the mega-event. This data collection resulted in Twitter social network datasets and socio-grams for each hash tag, which helped depict the state of the social media communities and information on the users within each community.

Through NodeXL, SNA provides insights into asocial media community via individual socio-grams, which can display a particular point in time. A series of socio-grams can also help determine how a community develops and transforms over time. For this study, the hash tag socio-gram series portrayed the hash tag tweets and assess the number of users and relationships that emerged each day and collectively during the examined time period. The study used the resulting data to address the following research questions.

3.3 Data analysis

RQ1 What social media communities formed during the 2014 Winter Olympic Games?

First, the series of socio-grams created via NodeXL displayed each social media community’s growth over the 19 days. The researchers reviewed the socio-grams and their accompanying frequency tables, which displayed the number of Twitter relationships (i.e., tweets) occurring daily within each community. Second, they examined the top tweets posted (and re-tweeted) each day in order to determine whether these messages coincided with variations in the community’s growth. Third, they explored the top Twitter users based on the most popular tweets. Information about each user’s number of users following, number of users followed, and number of tweets posted as well as Twitter biography helped


determine what potential effects they may have had on the community’s development.

RQ2 What similarities and differences emerged among the social media communities?

A comparative analysis of the data obtained for each social media community as outlined above helped assess potential similarities and differences among the three communities overall and on a daily basis during the period under examination.

4 Results

The study used SNA to examine social media activity occurring during the 2014 Winter Olympic Games, and the first research question asked what social media communities formed.

4.1 The #WeAreWinterSocial media community

4.1.1 Socio-grams

A series of sharp peaks and valleys characterised the #WeAreWinter social media community’s growth. The socio-grams reflected this activity, starting on February 7 with an array of activity spread throughout the network and some clustering in the centre (Figure 1). The smallest number of tweets occurred on February 11 with 837, and the highest occurred on February 17 with 5,732. The February 11 community contained fewer members and less hash tag usage. On February 17, an increased amount of clustering formed in the community’s centre as this activity unfolded. Additional peaks occurred on February 12 with 5,281, and February 21 with 5,362, respectively. Near the conclusion of the Olympic Games, the February 24 socio-gram revealed a decrease in Twitter activity compared to the two previous socio-grams, but greater than the first day. This change reflected the continued conversation occurring within the community, but with less fervour than during the middle of the mega-event. Finally, a sharp drop-off occurred on February 25 with 1,143 tweets.

4.1.2 Top hash tag tweets

The top tweets posted during this time period reflected the peak activity. Twitter user @CDNOlympicTeam had the most frequently re-tweeted messages, and the top four re-tweets came from this account (Table 2). Each message provided information about the Canadian team’s performance. The most popular tweet occurred on February 10 and received 772 re-tweets: “GOLD: [link] @Speedskater01 is 1500 m Olympic short track champion #WeAreWinter [link]. Other popular messages from this account generated more than 600 re-tweets. These included the February 17 message re-tweeted 753 times: “[link] Silver for Tessa & Scott in ice dance. #WeAreWinter [link]”. On February 18 readers re-tweeted another popular message 611 times: “RT @CDNOlympicTeam: [link] SILVER! @mike_riddle medals in first Olympic ski halfpipe competition #WeAreWinter [link]”. The account’s February 13 message received 608 re-tweets:


“@CDNOlympicTeam: Smooth start. Canada beats Norway 3–1 on Thursday night at #Sochi2014 [link] #WeAreWinter [link]”.

Figure 1 Evolution of the #WeAreWinter social media community, (a) 7 February (b) 11 February (c) 17 February (d) 24 February (see online version for colours)

(a) (b)

(c) (d)

Table 2 Top tweets by social media community

Community Date Count Tweet #Winter 2/10/14 772 RT @CDNOlympicTeam: GOLD: http://t.co/SCOd1RnEQi

@Speedskater01 is 1500 m Olympic short track champion. #WeAreWinter http://t.co/GNog93T0…

#Winter 2/17/14 753 RT @CDNOlympicTeam: http://t.co/AXJG0SDAby Silver for Tessa & Scott in ice dance. #WeAreWinter http://t.co/JyCCsh6bbQ

#Winter 2/18/14 611 RT @CDNOlympicTeam: http://t.co/bjX7XP0SEk SILVER! @mike_riddle medals in first Olympic ski halfpipe competition. #WeAreWinter http://t.c…

#Winter 2/13/14 608 RT @CDNOlympicTeam: Smooth start. Canada beats Norway 3-1 on Thursday night at #Sochi2014 http://t.co/6siCJR6yLe #WeAreWinter http://t.co…


Table 2 Top tweets by social media community (continued)

Community Date Count Tweet

#Cheers 2/8/14 297 RT @DelicateMartyr: #CheersToSochi http://t.co/95iwlsdLz4

#Cheers 2/16/14 248 RT @simonpegg: Please help support for LGBT during Sochi 2014 #CheerstoSochi, add a #Twibbon now! http://t.co/6cCeFDqggY

#Cheers 2/9/14 126 RT @sfpelosi: Fifth ring finally comes out ... #CheersToSochi (h/t @paragie) http://t.co/obUAiBUOZ9

#Cheers 2/7/14 61 RT @JoshADean: I wonder if @SarahPaIinUSA is watching from her porch #olympics #CheersToSochi

#Sochi 2/23/14 2,303 RT @Sochi_Problemz: That awkward moment when your shirt is supposed to say Canada. #SochiProblems http://t.co/jHVIEpPfOJ

#Sochi 2/24/14 1,622 RT @KiddJahmann: From Sochi With Love ! http://t.co/X3mIb0Rkag #SochiProblems #Sochi #Putin

#Sochi 2/21/14 782 RT @DrunkKane: The real reason we lost today.. #SochiProblems http://t.co/ZK8KCvFJnj

#Sochi 2/20/14 760 RT @k8ertotz: Wolf in my hall?!? #SochiProblems #SochiFail http://t.co/ZMqZFC40jp

4.1.3 Most popular users

@CDNOlympicTeam represented the most popular hash tag user based on its accrued re-tweets (Table 3). The entity’s Twitter biography stated “Official Twitter account of the Canadian Olympic Team” and included the hash tags #TeamCanada and #WeAreWinter. The Twitter account had accumulated over 18,795 tweets and over 313,000 followers, respectively, since its origination. This Twitter usage reflected an active account with a large number of readers, leading to a sizeable number of re-tweets with each message.

Table 3 Most popular social media community users

Community Twitter handle Following Followers Tweets Twitter biography

#Winter @CDNOlympicTeam 1,345 313,059 18,795 Official Twitter account of the Canadian Olympic Team. | Suivez-nous en français @OlympiqueCanada | #TeamCanada | #WeAreWinter

#Cheers @DelicateMartyr 1,438 1,187 11,507 Yet another Englishman in NY. I am responsible for what I say; not for that which you can understand. These views should be everyone’s. #yeshomo


Table 3 Most popular social media community users (continued)

Community Twitter handle Following Followers Tweets Twitter biography

#Cheers @JoshADean 646 406 1,335 Student Affairs Professional/Rodeo fan/Traveler/Writer/Realty TV Addict/Activist/Fearer of Sea Animals/Food and Drink lover

#Cheers @sfpelosi 1,235 10,651 31,783 American Dreamer #Cheers @simonpegg 648 3,877,066 13,216 Actor/writer - Spaced, Shaun

of the Dead, Hot Fuzz, Paul, World’s End. Also, secret agent, starship engineer and diesel weasel. GSOH. Must love dogs.

#Sochi @DrunkKane 3 64,034 297 My agent said I should start workin out. I said I am Patrick Fuckin’ Kane, you work out. You are fired. Parody.

#Sochi @k8ertotz 116 23,286 460 California bred and is a member of the US Olympic Luge team. I know all of Beyonce’s choreo by heart and I wear spandex for a living. Sochi 2014 shakaaaaaa

#Sochi @KiddJahmann 46 1,111 84 Mash-Ups, Music vidz, Commercials, Spoofs...Video

#Sochi @Sochi_Problemz 31 113,374 99 You think you have problems? Sochi has problems. Posting all the things wrong at the Sochi 2014 Olympics.

4.2 The #CheersToSochiSocial media community

4.2.1 Socio-grams

The #CheersToSochi social media community displayed moderate growth over the 19 days. February 7 revealed users spread around the network (Figure 2). The highest activity appeared on February 10 with 1,273 tweets, and the socio-gram reflected an increase in users at the centre and throughout the community. Conversely, the lowest amount of activity occurred the following day on February 11 with 298 tweets. The socio-gram revealed a sparser community, with a limited amount of clustering at the centre and a loose arrangement of members. The community witnessed an additional peak on February 17 with 1,121 tweets, and maintained a steady number in its remaining days. By February 24, the community looked similar to the first day with activity spread across its users, but a clustering of users still remained at the centre.


Figure 2 Evolution of the #CheersToSochi social media community, (a) 7 February (b) 10 February (c) 11 February (d) 24 February (see online version for colours)

(a) (b)

(c) (d)


The top tweets occurred early within the examined period with the highest number on February 8. The message “RT @DelicateMartyr: #CheersToSochi [link]” contained a satirical cartoon of the musical band Village People and featured Putin’s face superimposed over each band member’s face. Other popular re-tweeted messages included the February 16 tweet, which received 248 re-tweets: “RT @simonpegg: Please help support for LGBT during Sochi 2014 #CheerstoSochi, add a #Twibbon now! [link]”. Users re-tweeted the message 126 times on February 9: “RT @sfpelosi: Fifth ring finally comes out ... #CheersToSochi (h/t @paragie) [link]” with a link to a satirical article discussing the Olympics ring malfunction during the Opening Ceremonies. Finally, @JoshADean posted a message on February 7 and received 61 re-tweets: “I wonder if @SarahPalinUSA is watching from her porch #olympics #CheersToSochi”. This message referenced the former USA governor, Sarah Palin, who claimed she could see Russia from her home state of Alaska. Notably, peaks in the network did not coincide with the most popular tweets.



The four most popular Twitter users incorporating this hash tag had varied backgrounds per their Twitter biographies. Together they had an average of 972,328 followers and tweeted an average of 14,460 times. Twitter user @simonpegg had the most followers with over 3.9 million. The ‘actor/writer’ tweeted frequently with 13,216 tweets since opening the Twitter account. @sfpelosi, a self-described ‘American dreamer’, had the second-largest number of followers with 10,651 and proved an active Twitter user with 31,783 tweets. @DelicateMartyr described himself as ‘yet another Englishman in NY’ with 1,187 followers and 11,507 tweets. ‘student affairs professional’ @JoshADean had the smallest number of followers with 406 and tweeted 1,335 times.

4.3 The #SochiProblemsSocial media community

4.3.1 Socio-grams

A series of sharp peaks and valleys characterised the#SochiProblems social media community. The February 7 socio-gram showed a large amount of activity, but a relatively even spread across the community (Figure 3). The lowest number occurred two days later on February 9 with 858, and the socio-gram featured a sparser array of users. The highest number of tweets occurred on February 23 with 6,520. A large cluster of members appeared in the upper-right portion of the community, and this convergence depicted the viral nature of tweets exchanged with the #SochiProblems hash tag on this day. Additional peaks occurred on February 8 with 4,529 and February 22 with 4,951, respectively. However, a sharp drop-off occurred on February 24 with 1,826. The community revealed a large cluster with a small number of network members operating on the periphery.


The most popular tweet hailed from @Sochi_Problemz and contained a picture of three females stating, “That awkward moment when your shirt is supposed to say Canada #SochiProblems [link]”. The post generated 2,303 re-tweets and occurred near the end of the examined period on February 23. @KiddJahmann posted the second most re-tweeted message, which included a link to a YouTube video and stated “From Sochi With Love! [link] #SochiProblems #Sochi #Putin”. Occurring near the end of the 19-day period on February 24, the message contained a cartoon image of Putin dancing and received 1,622 re-tweets. The third most popular tweet came from @DrunkKane, who wrote “The real reason we lost today.. #SochiProblems [link]” and included a link to a photograph. Finally, @k8ertotz wrote “Wolf in my hall?!? #SochiProblems #SochiFail [link]” and embedded a YouTube video link. Television host and comedian Jimmy Kimmel later revealed that he partnered with Olympic competitor Kate Hansen to produce this content (Scott, 2014). One of the most popular tweets coincided with a peak in activity, while the others did not.


Figure 3 Evolution of the #SochiProblems social media community, (a) 7 February (b) 9 February (c) 23 February (d) 24 February (see online version for colours)

(a) (b)

(c) (d)


The four most popular Twitter users incorporating this hash tag featured a combination of individuals and entities. They had an average of 50,451 followers and tweeted an average of 235 times. Described as “posting all the things wrong at the Sochi 2014 Olympics”, @Sochi_Problemz had the largest number of followers with 113,374, and tweeted 99 times since opening its account. @DrunkKane, a parody account for National Hockey League (NHL) player Patrick Kane, also proved popular. The account had 64,034 followers and posted 297 times since its inception. Olympic luger #k8ertotz had 23,286 followers and 460 tweets. Finally, @KiddJahmann provided “mash-ups, music vidz, commercials, spoofs... video”, and had the smallest number of followers with 1,111 and tweets with 84, respectively.

4.4 Comparison of the social media communities

The second research question asked what similarities and differences emerged among the social media communities, which reflected varying levels of activity. The #WeAreWinter hash tag originated from an official Olympic Games entity, and arguably witnessed success – as measured by the number of tweets incorporating the hash tag, the number of


re-tweets each message received during the event and the connection between re-tweets and surges in community growth (Figure 4). The community forming around this hash tag remained relatively large, and saw spikes in activity based on the Canadian Olympic team’s performance. The other official social media community, #CheersToSochi, featured more stability, with fewer peaks and valleys in its activity. The community displayed less activity among its users, who employed activist and satirical messages to generate support for LGBT rights while poking fun at Putin. Finally, the #SochiProblems community emerged organically in response to perceived problems with the Olympic Games. Initially, the messages centred on amenities provided to journalists and others taking part in the event. The community eventually expanded to include a variety of other ‘problems’ – some fictional, others addressing actual issues. Again, this use of humour attracted a greater level of attention, as these messages often received the most re-tweets. The community expanded with this activity, and saw its largest growth occur towards the end of the event in response to humorous tweets as opposed to the official proceedings.

Figure 4 Daily social media community activity (see online version for colours)

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

#Winter

#Cheers

#Sochi

Overall, growth spurts occurred within the three communities, but all diminished in size as the Olympic Games concluded. Individuals and parody accounts often drove the conversation, as opposed to corporate organisations and media outlets. This would suggest Twitter offers potential benefits as a communications platform for a variety of users, whether those with millions of followers or only a few hundred, as evidenced by the most popular re-tweets. Some of these re-tweets coincided with an expansion in the corresponding social media community. Yet at other times the community activity featured a peak without one of these top messages, and this demonstrates the flood of messages exchanged within the communities – where even a message re-tweeted hundreds of time may have little to no effect on the network’s overall growth.


In terms of tweet content, most of the top messages contained links, whether to websites, photographs or videos. This similarity may point to an important characteristic of viral content – the inclusion of visuals to enhance the written message. Some tweets offered an explanatory message, while others simply provided a hash tag or two plus a link. Finally, some tweets received a significantly smaller number of re-tweets – or in most cases, no re-tweets at all. Despite a lack of response from other readers, users still felt compelled to post messages incorporating one of the three hash tags and take part in the larger conversation.

5 Discussion

This study examined social media communities forming during the 2014 Sochi Winter Olympic Games and the use of eWOM during this mega-event, and the findings provided a number of theoretical and practical implications.

5.1 Theoretical implications

The study explored eWOM occurring among social media communities during the 2014 Winter Olympic Games. The findings connect to previous sports-related research examining eWOM with social media communities, including those using Twitter to discuss sports organisations (Brown and Billings, 2013; Clavio et al., 2012; Hambrick and Sanderson, 2013). Previous research has also distinguished between the potential types of eWOM. PWOM occurs as fans and other social media users support some sporting events and participants (Blaszka et al., 2012; Frederick et al., 2013), while NWOM can emerge as users criticise others (O’Hallarn and Shapiro, 2014; Smith and Smith, 2012). In this study, PWOM existed alongside NWOM in the three Olympic Games social media communities. The #WeAreWinter marketing community reflected PWOM as Twitter user @CDNOlympicTeam and others promoted Canadian athletes and their competitive pursuits. Conversely, NWOM resulted within the #CheersToSochi hijacked community, which McDonalds first initiated to promote its sponsorship of the mega-event and activists later, took over to express their disdain for Putin and his refusal to support LGBT rights. Finally, the #SochiProblems organic social media community incorporated both PWOM and NWOM, as the community sometimes hosted humorous conversations and at other times highlighted negative circumstances surrounding the Olympic Games.

This study offers new insights as it examines the three message types – marketing, hijacked and organic – and supports the opportunity for further delineation within the PWOM and NWOM categories. Previous sports-related research focused primarily on organic messaging and the accompanying activities, which resulted in eWOM that was positive (Brown and Billings, 2013), negative (O’Hallarn and Shapiro, 2014) and mixed (Smith and Smith, 2012). These additional categories suggest the potential for extended use and research within SNS, as social media platforms continue to emerge and evolve, offering new and nuanced ways for sports consumers and other users to communicate.

In addition to exploring the conversations taking place, this study helped assess how quickly the information spread through the communities. Previous research has examined this diffusion process, whether with positive or negative information, and their results have proven mixed in determining which information type users spread or receive more


quickly (Arndt, 1967; Bayus, 1985; East et al., 2008). Thus, researchers have asserted the need to continue exploring social networks (Wang et al., 2013) and using SNA to understand the activities occurring within them (Bruns and Burgess, 2011). This study employed SNA to analyse the dissemination process in greater detail. The findings pointed to a faster spread of PWOM, as reflected by the relative growth of the #WeAreWinter community (PWOM) in comparison to the #CheersToSochi community (NWOM). The #WeAreWinter community accrued more followers and tweets, which suggests users were more inclined to share good news about the athletes and their performances as opposed to messages with a more serious or critical tone.

Researchers have used this SNA methodological approach to identify popular users within social networks, as these individuals can influence consumer perceptions and behaviours (Clavio et al., 2012; Hambrick and Sanderson, 2013; Smith et al., 2007). The findings revealed users with large follower numbers operated in concert with their less popular counterparts, who also accrued sizeable numbers of re-tweets. The results reflect a certain democracy within this social media environment, as users large and small had the opportunity to influence the community. Perhaps who spreads the message becomes less important when compared to what each user says.

5.2 Practical implications

As these findings show, the information dissemination process can occur quickly within eWOM settings. This speed may result from greater numbers joining the communities, as they seek to extend conversations beyond their local environments and connect with others who share common interests (Sahelices-Pinto and Rodríguez-Santos, 2014). The ability to have these messages magnified and distributed to a larger audience can occur within the SNS realm. Prior to the advent of social media, traditional media outlets and organisations commanded much of the attention and worked to provide information and news regarding events and other activities (Pegoraro, 2014). Social media in general and Twitter now more specifically gives users an opportunity to spread their messages. They can use SNS to seize upon a compelling topic or take a stance, and these activities have the potential to attract other readers.

SNS outlets also give users the ability to promote hash tags, slogans, and marketing messages. An opportunity exists for sports marketers and others to strategically use these messages to their benefit: by identifying those that resonate with users and prompting them to use them repeatedly. Yet they must prepare for the resulting conversations around their products and events (Ganim Barnes and Jacobsen, 2014). These discussions and the social media communities supporting them can sway consumer attitudes and behaviours both positively and negatively (Armstrong and Hagel, 2000; Sahelices-Pinto and Rodríguez-Santos, 2014). Thus, sport marketers should continuously monitor these communities, whether initiated formally or arising more organically among social media users. Those seeking to promote their messages should give consideration as to how they will be interpreted and how consumers will respond to them – thinking of best-case scenarios with PWOM marketing messages versus worst-case scenarios with NWOM hijacked and organic ones.

While NWOM did not spread as rapidly as PWOM with the Winter Olympic Games social media communities, the potential for detrimental effects still exists. Negative messages could influence consumer decisions, including in this context to not visit Russia nor consume products from McDonalds and other companies sponsoring the mega-event.


Users also incorporated satirical messaging in conjunction with some negative eWOM, perhaps to soften their criticism by poking fun at or making light of certain issues. This negative eWOM can increase awareness beyond the intended activities, such as using sport as a platform to discuss other issues. Sport marketers and organisers should recognise these potential uses and prepare to react accordingly to protect their brands while also addressing consumer needs and criticisms.

6 Limitations and future research

Limitations exist with the current study. First, the study looked at one major sporting event, the 2014 Sochi Winter Olympic Games. Examining other major or smaller events may have yielded different results. Next, the study explored three hash tags introduced during the event and receiving international exposure. Looking at other hash tags with a more regional or sports-specific focus may have yielded different results. Finally, the study examined the conversations within the Twitter environment. Exploring other social media platforms may have provided different results.

Future studies can extend this research to include other major or smaller events – for example, with sports or activities that do not receive as much attention on a national or international level. Research could incorporate the use of additional hash tags or marketing slogans. For instance, during this same mega-event hash tags such as #Sochi2014, #Russia, and #Olympics appeared among the tweets examined in this study. An exploration of how online communities developed around those messages could provide additional insights, as they also demonstrate the potential for PWOM and NWOM as users discuss a variety of topics via social media. Finally, studies could expand to include other platforms such as Facebook, YouTube and Instagram, which also have a presence during such events. An exploration of the pictorial and video content associated with these platforms could offer additional findings.

7 Conclusions

The 2014 Sochi Winter Games witnessed a marked increase in social media usage in comparison to the 2012 London Summer Games, which journalists and others declared ‘the Twitter Olympics’ (Whiteside, 2014). This study examined the emergence of three social media communities during the 2014 mega-event. Using the WOM conceptual framework and SNA, the study explored messages containing one of the following hash tags – #WeAreWinter, #CheersToSochi and #SochiProblems. The resulting social media communities revealed similarities in terms of peaks and valleys in their growth over time. This growth sometimes coincided with viral tweets, and the most popular messages contained celebratory or satirical content. While these frequently re-tweeted messages created some growth spurts, the communities still experienced declines as users eventually shifted their focus away from these conversations. In all three cases, the communities decayed as the Olympic Games concluded. These findings demonstrate the tenuous hold social media messages have on a user’s attention, but demonstrate the effects of PWOM and NWOM on audiences within these online environments.


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