The purpose of this paper is to explore consumer attitudes towards ambush marketing and official event sponsorship through the lens of sentiment analysis, and to examine social media users' ethical responses to digital event marketing campaigns during the 2018 FIFA World Cup.
The study employed a sentiment analysis, examining Twitter users’ utilization of sponsor and non-sponsor promotional hashtags. Statistical modelling programme R was used to access Twitter’s API, enabling the analysis and coding of user tweets pertaining to six marketing campaigns. The valence of each tweet – as well as the apparent user motivation underlying each post – was assessed, providing insight into Twitter users’ ethical impressions of sponsor and ambush marketer activities on social media and online engagement with social media marketing.
The study’s findings indicate that consumer attitudes towards ambush marketing may be significantly more positive than previously thought. Users’ attitudes towards ambush marketing appear significantly more positive than previously assumed, as users of social media emerged as highly responsive to creative and value-added non-sponsor campaigns.
The findings affirm that sentiment analysis may afford scholars and practitioners a viable means of assessing consumer attitudes towards social marketing activations, dependent upon campaign objectives and strategy. The study provides a new and invaluable context to consumer affect and ambush ethics research, advancing sponsorship and ambush marketing delivery and social sponsorship analytical practice.
Burton, N. (2019), "Exploring user sentiment towards sponsorship and ambush marketing", International Journal of Sports Marketing and Sponsorship, Vol. 20 No. 4, pp. 583-602. https://doi.org/10.1108/IJSMS-03-2019-0026Download as .RIS
Emerald Publishing Limited
Copyright © 2019, Emerald Publishing Limited
Contemporary sponsorship practices have increasingly embraced social, digital and mobile marketing practices as a means of activating partnerships with engaged audiences. Within sport, micro-blogging network Twitter represents an integral component of such strategy, affording brands a means of communicating content directly with target markets (Meenaghan et al., 2013), and driving brand discourse and facilitating engagement and interaction with consumers (Billings, 2014). Importantly, however, this trend has equally extended to ambush marketers, whose efforts to parallel official sponsorship communications have increasingly been targeted towards online campaigns (Chanavat and Desbordes, 2014; McKelvey and Grady, 2017). Non-sponsors have sought to capitalize on the real-time activation opportunities and largely unrestricted communications space available to non-sponsors, driving associative marketing campaigns in an effort to exploit the commercial value of major sporting events (Burton and Chadwick, 2018).
Historically, perspectives of ambush marketing have been informed by a rights-holder-driven perception of ambushing, depicting the practice as a parasitic attack on official sponsorship (Burton and Bradish, 2018; Burton et al., 2018). This depreciatory view of ambushing has inspired a body of research in the marketing and sponsorship literature examining consumers’ ethical impressions of ambush activities, fixated on consumers’ ethical appraisals of ambushing. This attitudinal ambush marketing research, however, is in need of significant advancement. The methods commonly employed to assess consumers’ ethical impressions have potentially biased results, weighting consumer impressions towards more ethically conscious views: survey questionnaires of consumers have most commonly been used, yet present a high possibility of representation, measurement and sampling biases (Hoek and Gendall, 2003), whilst the specific wording of survey items has been shown to be leading and has been acknowledged as potentially influencing respondents’ answers (Shani and Sandler, 1998). Moreover, despite these biases a prevailing antipathy on the part of consumers is evident (Lyberger and McCarthy, 2001; Portlock and Rose, 2009), as contrasting findings have restricted our understanding of consumers’ ethical impressions of ambushers and sponsors.
Social media, though, may provide a means of advancing ambush affect research. The study of consumer sentiment has been theorized as a potential metric for social sponsorship effectiveness (Meenaghan et al., 2013), affording a lens for scholars and practitioners to examine affect and user response. Sentiment analysis enables marketers to assess and evaluate user impressions of and attitudes towards brands, products and campaigns, based upon the emotions, cognitions and conscious or unconscious processes uncovered within texts (Ledoux, 1996). As such, the study of user sentiment offers a lens into consumer affect and impression, and may afford researchers and practitioners greater insight into social marketing effectiveness and affect.
This study therefore seeks to advance and contemporize ambush marketing attitudinal research by taking an exploratory approach in examining Twitter users’ responses to sponsorship and ambush marketing activities during the 2018 Fédération Internationale de Football Association (FIFA) World Cup Finals. Given Twitter’s prominence in sport and sport marketing (Billings, 2014), and users’ propensity for sharing opinions and sentiment (Jansen et al., 2009), the platform represents an ideal context for sentiment study. In examining users’ impressions of sponsor and non-sponsor campaigns online, and exploring the motivations behind consumer use of promotional hashtags, the present study offers new insight into consumers’ views and attitudes towards ambush marketing, and to afford an important new direction for ambush affect research.
Sponsorship and social media
The advent and rise of social media networks as platforms for marketing communications represent a significant opportunity for theoretical advancement in sponsorship and ambush marketing sentiment research. Media such as Facebook, Instagram and Twitter afford researchers a breadth and depth of insight into marketing communications practices, efficacy and impressions (Hennig-Thurau et al., 2010), and have inspired a growing line of research across industries, disciplines and applications. In turn, social media marketing has been acknowledged and embraced as a significant and viable element of integrated marketing communications (Keller, 2016). Scholars have emphasized the potential implications of user-generated content business and marketing theory and practice, included targeted advertising (Zhang and Katona, 2012), improved brand communications (De Vries et al., 2012) and increased customer engagement (Calder et al., 2015).
The effectiveness of marketing through social media channels has been examined and theorized around a variety of strategies and tactics, including the use of imagery or photographs (e.g. Hansson et al., 2013; Kwok and Yu, 2013; Sabate et al., 2014), the importance of interactivity and consumer engagement (Burton and Soboleva, 2011), the development of humorous, philanthropic or entertaining social media channels and posts (Cvijikj and Michahelles, 2013; Zhang et al., 2011), and the ability to create meaningful relationships with users allowing for feedback and information sharing between brand and consumer (Jansen et al., 2009). These findings have been reinforced by examinations of consumer motivations for engaging on social media, which have affirmed the important role and opportunities social media platforms play for brands and organizations in interacting and communicating with consumers across a variety of levels, including aspirational goals, passion, community creation and sharing, and identification creation (Stavros et al., 2014).
Within sponsorship, Twitter has become central to many of these efforts, particularly in sport (Santomier, 2008). As Hardin (2014) noted, Twitter is “highly complex when we consider the scope of its users, increasing technological capabilities of its interface, its integrated functions (e.g. breaking news and marketing), and the role that it plays in the wider interpersonal-mass communication landscape” (pp. 114-115). Although smaller in reach and user figures than the likes of Facebook and Instagram, Twitter’s role as a niche medium within new media networks has seen it embraced by sport fans and organizations (Billings, 2014), providing brands and users access to information, community creation and content distribution. Estimates suggest that up to half of all Twitter activity is sport related (Smith, 2013), frequently employed by brands, organizations and fans for real-time news, engagement-driven content sharing and dialogue facilitation (Pegoraro, 2014; Stavros et al., 2014).
As such, digital activations and consumer connection have become central to many sponsorship campaigns, including and especially in activating sporting partnerships and in engaging with sport fans. Scholars have argued that social media marketing presents an effective and valuable means of accessing and engaging with sponsorship audiences (Weeks et al., 2018), whilst as a provider of real-time “parasocial” relationships (Sanderson, 2014), Twitter represents a fundamental component of contemporary sport communication and marketing.
For sponsors, therefore, Twitter represents an important communications means for leveraging sponsorship-linked marketing campaigns, as well as for driving sponsorship analytics and insight (Meenaghan et al., 2013). The growth of social media as platforms for marketing communications and consumer engagement has inspired improved insights into the efficacy and reach of advertising campaigns resultant from the wealth of data analytics afforded by social media marketing, alongside greater interaction with consumers and new, more timely and responsive communications means. As Stavros et al. (2014) argued, “social media also are particularly well-suited to engagement within brand communities and therefore appeal to marketers seeking to understand those communities as most conversations occur in real-time and can be instantly digitally archived” (p. 458).
User motivation and social media engagement
As a result of this growth and acknowledged potential of social media as a communications platform, a parallel line of research has emerged exploring the motives and behaviours of social media users. Throughout, scholars have sought to examine user behaviours framed within the context of fans’ and consumers’ psychological motivations (cf. Mangold and Faulds, 2009; Seo and Green, 2008; Wann, 1995). Importantly, a distinction should be made between typical socially driven inter-user communications, and user engagement with or regarding brands in digital settings. In this respect, user motivation for brand engagement has been theorized to align closely with traditional word of mouth (WOM) models (Fay and Larkin, 2017; Mangold and Faulds, 2009), leading to the development of a growing body of electronic word of mouth (eWOM) research.
Within a sporting context, much of the extant user motivation behaviour research has been framed around fans’ engagement with athletes on social media platforms (e.g. Clavio and Kian, 2010; Hambrick et al., 2010; Witkemper et al., 2012), as well fans’ consumption of specific team or league social media outlets (Seo and Green, 2008; Stavros et al., 2014). Fans’ affinity towards an athlete or team, as well as the heightened interactive and engagement opportunities presented, has been noted as central motivators (Clavio and Kian, 2010; Frederick et al., 2012), informed by Seo and Green’s (2008) seminar examination of online fan behaviours and development of the Motivation Scale for Sport Online Consumption. Drawing upon psychology, marketing and consumer behaviour literature, the authors constructed a ten-dimension scale mapping users’ motives and constraints for consuming team-owned websites, and provided a model of user motivations ranging from information gathering to economic benefits. Stavros et al. (2014) further expanded upon this research, exploring user motivations on social media within the context of four proposed central motives: passion, hope, esteem and camaraderie. The proposed motives drew upon social media’s proposed value co-creation between user groups (Filo et al., 2015), affording a multi-faceted and layered view into users’ reasoning and aspirations when consuming and engaging with sport organizations digitally.
To date, however, there remains a dearth of theoretical investigation into fans’ motivations for engaging with sport brands online; rather, much of the contemporary study of social media sponsorship engagement and activation has centred on the strategic competencies and directions of brands themselves (Gillooly et al., 2017; Ko et al., 2017). This thus represents an important area of research in need of further development. Within the broader social media motivations literature, consumer sharing behaviours and motivations – alongside users’ direct engagement with brand accounts online – has been found to be driven by content type and brand-post characteristics, as well as social motives and users’ attitudes towards a specific brand, property or event (Borges-Tiago et al., 2019). The virality and transcendence of social media messaging, however, remains firmly rooted in traditional and eWOM theory, yet affective dimensions such as enthusiasm or celebratory behaviours have been noted as drivers of brand and message sharing (Hambrick and Pegoraro, 2014). Indeed, as a vehicle and platform for eWOM and brand sharing, user sentiment has been suggested to be a primary motivator (Fay and Larkin, 2017), thus meriting further study.
Valence and sentiment in sponsorship research
One means of exploring user engagement and driving sponsorship insight online suggested is in examining consumer sentiment towards brands and campaigns through sentiment analysis (Meenaghan et al., 2013). Also known as polarity analysis or opinion mining (Mostafa, 2013), sentiment analysis describes the analysis of individuals’ opinions, emotions and attitudes towards a brand, product, campaign or other property (Liu, 2012). As the subfield of natural language investigation and processing, the practice has proven in recent years to be an effective tool across a variety of industries and disciplines, including politics, economics, healthcare and urban planning (Roberts et al., 2018; Yu and Wang, 2015), seeking to analyze individuals’ emotions, opinions, attitudes or perceptions towards a specific entity, product or issue (Liu, 2012; Liu et al., 2017; Yu and Wang, 2015).
Inherent to this process is the understanding and analysis of attitudes, and the assertion of valence to consumers’ statements or social media posts aligning with positive, neutral or negative attitudinal states. Taken from psychology theory to refer to the inherent “goodness/attractiveness” or “badness/averseness” of a subject, the successful evaluation of attitude valence presents a potent performance indicator of brand building. Textual data are coded classified as positive, neutral or negative (Liu, 2012; Pang and Lee, 2008), thus affording researchers the ability to assess and aggregate consumers’ sentiment towards a phenomenon.
The mining of sentiment via social media therefore presents scholars and practitioners with a substantial opportunity for investigating users’ feelings and emotions (Cooke and Buckley, 2008). A significant proportion of social media discussions has been found to relate to expressions of opinion or sentiment related to products or brands (Jansen et al., 2009); Twitter users regularly share real-time responses, emotions and attitudes (Ji and Raney, 2014; Wang, 2013), enabling brands to identify specific consumer impressions and preferences, as well as to analyze longer-term trends and to better target advertising efforts (Mostafa, 2013). Moreover, as a micro-blogging network, Twitter offers researchers short texts (up to 280 characters) expressing ideas, opinions or thoughts, thereby facilitating valence isolation and analysis.
For sponsorship, however, the mining of consumer sentiment and response to a marketing campaign remains a largely untapped resource. Ambush marketing and sponsorship research into consumer impressions has commonly relied upon ethical and moral biases, investigating the perceived effect of fans towards ambushing. In this respect, the extant ambush literature has provided merely a cross-sectional view of consumer ambush impressions, limited by antiquated and biased conceptualizations of ambushing, and inadequate data collection methods. Despite the majority of ambush ethics studies taking a specific focus on a particular event (e.g. the Olympics, FIFA World Cup or NFL Super Bowl) and incorporating ambush awareness metrics in order to associate particular brands or known ambushers in the minds of respondents, the vast majority of consumer-focussed ambush research to date has explored ambushing in the abstract. Researchers have relied upon fictitious brands and ambush scenarios in their analyses, removing the real-world element of brand impressions, ethical biases and brand schema. Participants throughout have been canvassed on their opinions of ambushing as a concept – framed as parasitic or amoral – rather than presented with explicit examples or cases upon which to base their evaluations.
Nevertheless, the ethical framing of ambush marketing has succeeded in guiding ambush scholarship towards moral and ethical perspectives. Myriad studies have explored ambushing through the lens of ethical representation and perspectives, most frequently investigating consumers’ attitudes and opinions towards ambushing through affect surveys (e.g. Dickson et al., 2015; Portlock and Rose, 2009). Unfortunately, however, the extant ambush affect research has proven largely inconclusive; contrasting results have suggested that consumers’ views of ambushing weaken in response to perceived ambush tactics (Mazodier and Quester, 2010), yet offer little moral objection to ambushing in competitive marketing environments (Moorman and Greenwell, 2005; Shani and Sandler, 1998). Moreover, respondents’ views of ambushing have been theorized to be guided by context (Leonidou et al., 2010), such as one’s involvement with an event (McKelvey et al., 2012), or perceived industry advertising standards (Dickson et al., 2015).
Across different events, demographics and contexts, consumers appear at best moderately opposed to ambush marketing, at worst entirely unaware and uncaring of the distinctions that exist between sponsors and ambushers, and the purported deleterious effects ambushers have on sponsorship returns. Results have been inconsistent and have offered little insight into true consumer perspectives of ambushing (e.g. Dickson et al., 2015; Lyberger and McCarthy, 2001; Séguin et al., 2005; Portlock and Rose, 2009). Rather, as Koenigstorfer and Groeppel-Klein (2012) theorized, “without negative counter-ambush communications or ‘stigmatizing public disclosure’, sport consumers’ attitudes may not be affected by their general sense that a brand’s ambush behavior is inappropriate or unfair” (p. 490). Perhaps most disconcerting, though, such studies have overlooked other aspects of attitude and antecedents to consumer affect in favour of such ethical positioning, limiting the reach and scope of ambush research, and calling into question the relevance of ambush ethics research Crompton (2004).
Moreover, recent research has shown that rights holders’ efforts to ethically frame ambush marketing discourse were a strategic direction taken in the earliest years of ambush practices (Burton and Bradish, 2018), intended to guide public opinion and consumer sentiment on ambushing in an apparent effort to frame ambush marketing as an offensive or detrimental practice (Burton et al., 2018; Burton and Bradish, 2018).
Evidence suggests, however, that implicit brand memory effects may be more prominent than those explicitly shared in traditional methods (Schmidt et al., 2018), and thus merit greater study. In this respect, sentiment analysis may provide researchers and practitioners with a more accurate view of consumers’ opinions, and thus afford improved metrics for online sponsorship activation and affect. Given the emphasis within sponsorship on consumers’ affective response to sponsorship (Prendergast et al., 2016), and the contradictory and inconclusive body of research into consumers’ attitudinal response to sponsorship and ambush marketing (Moorman and Greenwell, 2005; Portlock and Rose, 2009; Shani and Sandler, 1998), such advances represent important considerations for sponsorship theory and practice. Given the managerial and political ramifications of ambush marketing prevention incumbent upon host jurisdictions, event organizers and official sponsors, greater investigation into specific consumer impressions and attitudes is required.
As such, this research seeks to explore and advance ambush and sponsorship affect scholarship, addressing two central research questions:
To what extent does sentiment analysis measure consumer impressions and affect towards ambush marketing?
Does consumers’ engagement with ambush marketing campaigns reflect an explicit ethical perspective?
In so doing, the study examines both the prevailing sentiment and valence of user engagement with promotional hashtags, as well as the underlying motivation of users in sharing brand hashtagged posts. Taking an exploratory approach, the study’s methods draw on and adapt Twitter sentiment analysis research for digital marketing campaigns, examining user opinions of campaigns staged by both sponsors and ambushers during the 2018 FIFA World Cup Finals.
Data collection was conducted over a six-and-a-half-week period beginning 7th June, one week prior to the commencement of the 2018 FIFA World Cup Finals, and terminating 22nd July, one week following the tournament’s close. To facilitate data collection and analysis, Twitter data were accessed from Twitter’s standard API using Kearney’s (2018) “rTweet” package for open source programming and statistical analysis language R. Following Vorvoreanu et al.’s (2013) approach, selected brands and campaigns were identified prior to the group stages of the event as target non-sponsors and sponsor controls to be monitored and examined, each boasting a promotional hashtag allowing for relevant public discourse and engagement on Twitter to be collected. Data were extracted through rTweet’s Twitter data scraping function following each day of the collection period, whereupon data were exported as Microsoft Excel .csv files to facilitate analysis.
The campaigns selected for hashtracking were chosen based on a number of criteria: first, both sponsors and non-sponsor marketers were identified based upon a preliminary document analysis of marketing and advertising press and trade publications detailing World Cup-themed advertising efforts throughout the Spring of 2018. This document analysis offered practical insight into those campaigns to be run throughout the 2018 tournament, as well as specific detail regarding the media employed by the brands and tactics employed component to the campaigns. Second, prospective campaign criteria included: a multi-national, English-language activation of the campaign; a clear and verifiable link or allusion to the FIFA World Cup; and a bespoke hashtag promoted by the brand component to the campaign. Importantly, the hashtag promoted needed to be unique to the World Cup campaign, and not one regularly used by the brand more generally (e.g. #JustDoIt from Nike was excluded). This was an important distinction to maintain in order to concentrate data collection and analysis on the specific advertising campaigns, rather than the brands more holistically.
The selection of Twitter as the target platform was guided by a number of considerations: first, whilst other social media platforms (e.g. Instagram, Snapchat) are emerging as central communications tools for brands in social marketing, Twitter remains a primary social platform for brand activation and engagement in sport marketing (Pegoraro, 2014; Stavros et al., 2014). Additionally, amongst those social media platforms employed by sponsors, Twitter affords the greatest interactivity and inter-user engagement, thus enabling the study to examine hashtag use and non-sponsor-led discourse amongst users. Whilst comments on YouTube or Instagram posts may an alternative means of gaining insight into individuals’ affective response to sponsor and non-sponsor campaigns, the tracking of hashtags through Twitter’s API was determined to provide the broadest and fullest data corpus for analysis.
In total, six campaigns were ultimately selected for analysis (see Table I). It is notable that typically prominent ambushers of the FIFA World Cup such as Nike, Pepsi and Bavaria were not included in the study’s sample. Nike was conspicuously silent throughout the tournament, creating tailored, bespoke national campaigns in lieu of the more standard, global master creative campaigns that the brand has employed previously around major events (Beer, 2018). Likewise, Pepsi eschewed a more traditional approach to marketing around the World Cup, instead centring their “Love It, Live It” campaign through the Spring of 2018 centred around their sponsorship of the UEFA Champions League (McCarthy, 2018).
Data collation and cleansing
Upon completion of the data collection process, individual daily brand subsets were unified into six bespoke data sets containing each specific campaign. The resultant data sets were then cleansed to include only users’ Twitter name, the content or text of each tweet captured, the number of likes and retweets earned by the tweet, and the handle of the user to whom the tweet may have been directed in reply, across five columns. A pre-coding of the data corpus was then conducted to ensure that data were filtered to remove retweets, duplicate tweets, and extraneous and unrelated uses of the hashtags (Lucas et al., 2017); these included overt and explicit cases of hashjacking, wherein individuals or entities used the hashtags tracked in an effort to derail or divert online conversation towards a different proprietary topic or entity (Pegoraro et al., 2014). The study’s data collection and analysis were delimited to English and French tweets following the cleansing process, in order to facilitate analysis and to reflect the languages spoken by the research team. As such, throughout this pre-filtering process, tweets in other languages were excluded from the final data sets used for analysis.
Furthermore, given the study’s specific interest in user discourse regarding and surrounding sponsor and non-sponsor campaigns and the affective response of consumers to social media activations, only those tweets from personal Twitter accounts were included in the final analysis. All tweets sent from corporate-owned and brand-led accounts were removed and excluded from the final analysis; this included promotional tweets from endorsers, as in the case of Visa’s activation for #PayLikeZlatan incorporating Swedish star footballer Zlatan Ibrahimovic, or Umbro’s partnership with comedian Brett Domino. These were identified through a manual cleansing of the data, specifically identifying and excluding brand-owned accounts and Twitter-verified endorser accounts (included within the data extraction through rTweet). Promotional tweets from other organizations or corporate entities seeking to piggy-back on the reach of the hashtags collected, as well as overt examples of individuals seeking to align separate causes or events through the use of the sponsor or non-sponsor’s hashtag, were likewise removed (Visa’s Twitter promotion #PayLikeZlatan, for example, was frequently used in tweets discussing and debating the Kenyan budget). Finally, tweets containing only the hashtag and no other content or text were excluded from the final sample, in order to better focus the analysis and more accurately reflect the valence of tweets collected.
The final sample contained 2,136 total tweets from 1,214 unique users: 1,723 tweets containing official sponsor hashtags, and 413 containing non-sponsor hashtags. Whilst no agreed sample size has been delimited in Twitter sentiment analysis research to date, the final sample fitted with previously set benchmarks (e.g. Canhoto and Padmanabhan, 2015; Lucas et al., 2017; Taecharungroj, 2017; Yu and Wang, 2015) and provided ample data for analysis.
Whilst machine-learning sentiment analysis tools have received increased attention and greater use in scholarly works recently, a dual-coder manual approach was adopted for the study in order to better capture the nuances and complexities of each post, and to more accurately assess the valence and sentiment of each tweet. Extensive research has been conducted into the reliability of automated sentiment analysis tools (e.g. Canhoto and Padmanabhan, 2015; Giachanou and Crestani, 2016; Roberts et al., 2018), yielding an emerging consensus that machine-learning and automated sentiment mining and analysis pose a number of risks for researchers. Across a number of automated sentiment analysis tools, significant, consistent errors have been found (Canhoto and Padmanabhan, 2015). Findings suggest that negative and neutral tweets are more likely to be correctly identified and annotated than positive tweets by automated systems, thus potentially biasing results (Lucas et al., 2017).
Arguments against manual annotation typically concern time and resources, dependent on the volume of tweets to be analyzed (Roberts et al., 2018). However, manual annotation has been shown to provide the most reliable method of analyzing user sentiment, as individual human annotators are more able to correctly identify emotion, valence and tone in a given tweet (Saif et al., 2013). The improved accuracy in coding may in part be due to the nature of Twitter entries, which are characteristically brief (less than 280 characters), frequently boast abbreviations and slang, and may have errors in grammar, syntax or typing (Canhoto and Padmanabhan, 2015). Similarly, user sentiment varies across different cultures and with time, both in the style of delivery and specific linguistic modality (Abbasi et al., 2008). A comprehensive and accurate analysis of sentiment and valence in texts devoid of context thus may require a manual approach, particularly accounting for potential issues in textual analysis such as irony, sarcasm, punctuation or the increased use of emojis and GIFs (Mostafa, 2013).
As such, the two-coder manual approach adopted was determined to afford the most accurate and representative means of analysis given the nature of the data collected, the multi-lingual sample and volume of data to be coded. An initial sub-sample of 200 tweets was coded individually and separately by a two-member research team, coding each tweet by valence as either positive (+1), neutral (0) or negative (−1), following which Cohen’s κ was calculated in order to assess inter-coder reliability (Berry and Mielke, 1988). The team’s resultant κ coefficient of κ=0.752 (75.2 per cent) indicated strong agreement between the coders (Landis and Koch, 1977); the research team thus completed the analysis, dividing and coding each of the data subsets individually based on valence. The results were then gathered and collated, allowing for the overall sentiment of users towards individual campaigns – as well as ambush marketing and sponsorship activations more generally – to be calculated.
Upon completion of this sentiment analysis, a subsequent content analysis and pattern coding of the tweet data was conducted, following a similar manual coding process (Hsieh and Shannon, 2005). The two members of research team open coded the data based on apparent attitudes, sentiments and tweet characteristics (e.g. multi-media usage, engagement with other users and direct interaction with brands), guided by Stavros et al.’s (2014) four categories of social media fan motivation types: passion, hope, esteem and camaraderie. Adapting the four categories for brand-focussed social media statements (in lieu of team-centric fan engagements), the intent of this analysis was to initially determine how effective or accurate sentiment analysis may be in assessing consumer affect towards sponsor and non-sponsor online activations.
Each member again initially coded 200 tweets independently, whereupon the research team met to compare findings and to once again establish inter-coder reliability. The team’s κ coefficient was calculated as κ=0.812 (81.2 per cent), suggesting a strong agreement (Landis and Koch, 1977). The team then completed the open coding, assigning each tweet to one of the Stavros et al.’s (2014) categories whilst simultaneously identifying new and unique open codes for analysis. The research team then met again to construct a unified coding document which incorporated Stavros et al.’s (2014) four categories as well as two newly emergent categories: influence, drawing on Fay and Larkin’s (2017) “brand sharing” metric used to describe those users engaging in online content production or information sharing; and commentary, accounting for those tweets devoid of emotional connection or apparent motive, and instead intended to provide personal play-by-play or match punditry throughout matches. The two coders then coded the data corpus again independently, assigning each tweet to one of the six categories established.
Following this analysis, the research team then compared the valence of tweets against the six categories of social media engagement motivation, providing insight into the potential motivations of Twitter users in employing brand hashtags during a sporting event as well as the relative value of sentiment analysis in brand marketing online. Given the non-probabilistic nature of the data collection and cleansing, the intent of this analysis was not to draw inferences into a more generalizable or replicable population, but rather to assess and explore user sentiment and motivations within the specific context of the case examined. Statistical analysis of the sentiment analysis and user motivations findings revealed no statistically significant findings between the sentiment and motivation of tweets, potentially impacted by the purposive sampling employed in collecting and collating the Twitter data.
A number of preliminary results upon completing the analysis merit mention: first, upon cleansing the data of extraneous tweets and brand-led or endorsed content, there was a noticeable disparity in sample sizes between sponsor and non-sponsor campaigns. More than 500 brand-led or affiliated tweets were excluded from the final non-sponsor subsets, including an aggressive leveraging of the #MadeDefiant campaign by Beats By Dre, and partnerships with a range of athlete endorsers who activated the campaign on their own social media accounts.
Furthermore, it is notable that the non-sponsor campaigns included received considerably greater share of attention prior to and immediately following the finals tournament relative to the overall buzz received for the campaign when compared to the official sponsors. In the period leading up to the tournament included in the data collection process (7th–13th June), 35.84 per cent of all non-sponsor-hashtag usage occurred; by contrast, sponsors received only 7.13 per cent of overall buzz during this time. Similarly, in the week following the conclusion of the event, non-sponsors earned 6.54 per cent of their buzz as opposed to only 1.04 per cent for sponsors. As a result, during the staging of the finals tournament sponsors enjoyed 91.82 per cent of their hashtag usage.
Curiously, this predominance of sponsor-hashtag usage during the tournament was only tempered by an apparent absence of user engagement between 4th and 9th July. This period included the quarter-finals matches contested on 6th and 7th July, as well as tournament off-days following the round of 16 matches and immediately preceding the semi-finals. During this window, Twitter data collected containing official sponsor hashtags were exclusively brand-led or created by “bots”, and thus were excluded from analysis. Non-sponsors, by contrast, maintained a volume of engagement across these dates consistent with the rest of the tournament’s latter stages, suggesting that official sponsor engagement waned during this period singularly.
In calculating the average valence of both sponsor- and non-sponsor-campaign-related tweets, a noticeable difference in user sentiment is apparent. Across all sponsor hashtagged tweets, the overall sentiment scored 0.0801, suggesting a largely neutral view on the part of users (see Figure 1); non-sponsor campaigns, by contrast, received significantly more positive attention, yielding an average valence of 0.479. The distribution of tweets between positive, neutral and negative (see Figure 2) offers some clarity into this discrepancy: the valence distribution between sponsors and non-sponsors shows that whereas the majority of non-sponsor-campaign-related tweets were coded as positive – with only 12.6 per cent of non-sponsor-hashtag tweets coded as negative – sponsor-hashtag usage was overwhelmingly neutral, accounting for 68.89 per cent of all sponsor tweets collected.
This discrepancy between user sentiment towards sponsors and non-sponsors is magnified in examining each brand’s hashtag usage individually. Across the six campaigns explored, the three outside brands each scored higher than did their sponsor counterparts (see Table II). Again, each of the non-sponsors’ hashtags received significantly higher relative volume of positive sentiment displayed than did the sponsors’ campaigns, each of which averaged between 54.7 and 74.2 per cent neutral scores.
In subsequently analyzing the Twitter data based on user motivation, no statistical correlation was found between tweet valence and the six categories of user motivation for tweeting (see Table III). However, in looking at hashtag use between sponsors and non-sponsors, a number of patterns emerged worthy of mention, suggesting that a relationship between sentiment and motivation merits consideration (Table IV).
First, users appear to have predominantly used sponsor hashtags as proxy for official event hashtags, employing the campaign hashtags in match commentary and amateur punditry far more than those of ambushers. In total, 36.5 per cent of all sponsor tweets collected were from users engaging in match commentary or in-game punditry; a further 18.2 per cent were from users exhibiting community-directed and socialization tendencies, coded as camaraderie (Stavros et al., 2014). By contrast, only 17.7 per cent of non-sponsor tweets accounted for commentary or socialization combined, representing a significant difference in users’ motives and usage of brand hashtags. Budweiser, in particular, saw their campaign hashtag employed by Twitter users to connect with each other through match commentary: in total, 41.2 per cent of uses of #LightUpTheWorldCup came of in-game commentary and amateur punditry, more than twice the rate of Visa’s broadcast usage, for example.
Second, as illustrated in Figure 3, a disparity in user motivation and apparent sentiment behind sponsor and ambusher hashtag use was evident. Those sponsor tweets categorized as motivated by “esteem” – indicating “comments directed toward the [organization] and/or fellow fans that share positive or negative personal fandom experiences, or proclaim expertise and knowledge” (Stavros et al., 2014, p. 461) – weighted more heavily towards negative sentiment than in the case of non-sponsors. Sponsor campaigns were often referenced or explicitly named by users venting or sharing negative or derisory opinions; posts such as “Hey @budweiserusa, you can’t support Pride in the U.S. and the World Cup in Russia, where LGBTQIA+ people are constantly being persecuted. You have to choose: #PrideOverGenocide #LightUpTheWorldCup #ManoftheMatch #ThisBudsForYou” and “A 36 year old man who refers to himself in 3rd person […] #PayLikeZlatan”, highlighted at times negative or sarcastic sentiment voiced by uses, often directly responding to sponsor accounts.
By contrast, non-sponsors were more regularly praised and promoted by users – seemingly allied to users’ perceived value-added components of the campaigns. Umbro’s #EnglandAnthem, for example, benefited from England’s unexpected progress to the semi-finals, and tapped into English supporters’ optimism. The hashtag emerged alongside the unofficial catchphrase “It’s Coming Home” as rallying cries for England fans, driving much of the hashtag’s use during the latter stages of the tournament. Users embraced the campaign, regularly sharing the link to Umbro’s unofficial England song (“Now I’m excited for a non specific international football tournament! #englandanthem How To Make a Hit Football Anthem https://t.co/stn0xoucOb via @YouTube”), and even celebrating the subversive nature of the campaign (“What’s not to love about @BrettDomino’s #EnglandAnthem for a non specific international football competition?!”).
Irn-Bru similarly earned plaudits and positive WOM from users from their promotional giveaway of branded flip-flops, driving engagement and yielding an overwhelmingly positive user sentiment. Users shared photos of gift boxes delivered by Irn-Bru to contestant winners containing flip-flops, an orange football (reflective of the brand’s feature colours), and a chance to win a trip to the Maldives to watch the finals tournament. Comments such as “YASS! My @irnbru flip-flops turned up today! #BruPlane”, “What a great gift to get on a sunny morning Thanks @irnbru how did you know my shoe size? #OrangeIsMyFavouriteColour #BruPlane” or “My summer/life is now complete, I have won a pair of @irnbru flip-flops #BruPlane” typified the positivity surrounding Irn-Bru’s campaign amongst Twitter users.
Amongst non-sponsors, Beats By Dre’s overall neutrality is notable. Whilst the brand earned largely positive sentiment from users, Beats received an elevated proportion of esteem-motivated tweets, particularly related to the quality of the brand’s headphones, which ultimately impacted upon the average valence of the brand’s exposure. Nevertheless, the creativity and polish shown in the brand’s #MadeDefiant video ensured that users’ passion and influence were apparent: “@beatsbydre World Cup ad is a classic .@realguyritchie masterpiece #MadeDefiant”; “The kings of #ambushmarketing are back once again for #FifaWorldCup2018 @beatsbydre have made a really cool advert featuring the who’s who of world football and it is directed by Guy Ritchie #MadeDefiant”; and “this is how it should be done […] .EPIC from @beatsbydre #WorldCup #madedefiant”.
As the first examination of consumer sentiment towards social ambush marketing campaigns to date, the study’s findings offer a lens through which to examine sponsor and non-sponsor marketing around major events. Importantly, the findings presented here suggest that sentiment analysis may represent a viable tool for analyzing consumer attitudes and affect towards ambush marketing. This applicability of sentiment analysis to ambush marketing campaigns is further reinforced by the absence of ethical framing or consideration uncovered within users’ motivations for engaging with non-sponsor brands and using promotional hashtags. Rather, the positive sentiment shared by Twitter users across all three non-sponsor hashtags tracked is mirrored by predominantly positive motivations of influence and passion. This positive sentiment may suggest that consumers’ ethical impressions of ambushing have been largely overstated.
Implications for practice
For sponsors, the relative frequency of hashtag mentions between ambushers and official sponsors suggests that event partners still own a considerable advantage in maintaining consumers’ attention and engagement. Whilst the ambush campaigns selected for study earned significant bandwidth amongst users upon the launch of their campaigns and through the early stages of the tournament, that engagement waned markedly over the course of the event. Non-sponsor campaigns enjoyed greater share of voice prior to and immediately following the event; however, during the finals period sponsor campaign buzz significantly outweighed non-sponsor-hashtag usage. This predominance of sponsor engagement during the tournament is illustrative of the competitive advantage afforded to brands via official sponsorship, as well as the ability of brands to embrace and exploit new media’s role in contemporary marketing across myriad objectives and means (Gillooly et al., 2017; Mangold and Faulds, 2009).
In particular, sponsoring brands should be cognizant of online consumers’ usage tendencies of promotional hashtags, and should adopt evaluative social metrics accordingly. The retention of interest in sponsor campaigns throughout the event is reflective of sponsors’ success in driving online discourse and engagement – earning widespread use by Twitter users as mechanisms to centralize and connect match-related discourse. Indeed, across the three sponsors studied, in-match commentary accounted for over 36 per cent of all sponsor buzz. Although the result of this usage was a predominantly neutral sentiment towards the campaigns and hashtags studied, the extensive use by consumers and integration of individual campaigns into event discourse afforded sponsors greater engagement and market presence, and represent important metrics for social media marketing effectiveness (Burton and Soboleva, 2011). As such, opinion mining of sponsor-related tweets may require a more targeted and specific approach, with greater emphasis on those tweets directed at the brands themselves, or at users’ peers, where brand- and campaign-related sentiment was more regularly shared.
For those brands contemplating engaging in ambush marketing but wary of consumer sentiment, the findings presented here offer an optimistic view of consumer sentiment – contingent upon the delivery and efficacy of the association created, and the value added for consumers. Social media marketing has been found to be most effective when it is engaging and entertaining (Cvijikj and Michahelles, 2013); the likes of Irn-Bru and Umbro effectively utilized humour and creativity in their posts, and were consistently praised by users and succeeded in driving positive sentiment. Use of both hashtags and the response of users to the campaigns was largely motivated by sharing and promoting the campaigns to fellow users, both directly to followers in building Camaraderie, and more broadly acting as mavens in sharing the links widely as Influencers.
Similarly, Irn-Bru and Budweiser each earned considerable praise from users for promotional giveaways and experiential components to their campaigns, suggesting that value-added components incorporated within online campaigns may assist in driving sentiment and buzz, for both sponsors and ambushers. This aligns with previous research into sponsorship success in online environments (cf. Gillooly et al., 2017): sponsors have previously been shown to achieve considerable success in utilizing social media platforms through rewards-based activations. For prospective ambushers, then, identifying and executing significant value-added drivers as a means of engaging with their audience, within the legal confines of event rights management and sponsorship protection, may provide a means of integrating the brand into the broader marketing climate of the event.
Most importantly, the findings presented here provide insight into Twitter users’ motives for engaging with brands through promotional hashtags, and their affective reactions to social media marketing campaigns. The strategic intent behind hashtag creation and use in both sponsor and non-sponsor activations must be balanced in evaluating sentiment and hashtag use: if a sponsor intended for their hashtag to be used in match commentary by fans, a more neutral valence may be anticipated and accepted. By contrast, if a sponsor’s social media activations are tailored around product launches or promotional giveaways, user sentiment may offer a valuable tool for evaluation. In this context, brand perception and user discourse valence through digital marketing and social media activation can inform overall marketing strategy (Mostafa, 2013), by providing organizations with real-time feedback. Sentiment analysis affords practitioners an opportunity for direct interaction and meaningful engagement, yet must also be representative of the brand’s objectives and approach, as evidenced here.
Finally, for both sponsors and rights holders the predominantly positive attitudes held by users towards ambush campaigns present a possible concern. Much of the existing counter-ambush programming employed by rights holders is reliant on an assumed negative impression of ambushing held by consumers. Interventionist frameworks which have developed based on public relations and ethics-based campaigns against ambushing (such as “name and shame” PR tactics and publicly driven legislative frameworks) should, however, only be implemented strategically and with an awareness of context and fit. The disclosure and condemnation of ambush marketing brands in counter-ambush communications has been found to potentially impact negatively upon consumer perception of both sponsors and ambushers (Humphreys et al., 2010; Koenigstorfer and Uhrich, 2017; Mazodier and Quester, 2010). Given consumers’ positive sentiment towards ambush campaigns, event stakeholders should be strategic and deliberate in their use of such public appeals, and must not rely on consumer sentimentality or moral standing.
Conclusions and future directions
Ultimately, this study advances sponsorship and ambush marketing research by providing new context and clarity to ambush affect research. Foremost, there is evidence that consumers offer little moral or ethical objection to ambush marketing; absent the ethical biases of previous ambush affect studies, consumer sentiment towards ambushing appears to be significantly more positive than previously assumed, and indeed more favourable than that of sponsorship. The sentiment towards social ambush campaigns examined here suggests that previous moral and ethical concerns may have been overstated and misrepresented, necessitating a new approach to sponsorship and ambush marketing analysis moving forward.
In turn, further examinations of consumer response to, and engagement with, campaigns on competing social media platforms such as Instagram and Snapchat are required. Particularly given the divergent communications means and strategic uses of different new and social media tools, canvassing users’ affective responses and engagement with brands and brand campaigns across different media represents a potentially invaluable avenue for future research. Likewise, the present study’s delimitation to English- and French-language Twitter posts highlights the need for broadened international and multi-lingual examinations. To date, the cross-cultural impressions of ambush marketing have been introduced and examined within the context of specific target markets (e.g. New Zealand rugby supporters, Dickson et al., 2015; European football supporters, Burton et al., 2018); however, the present methods provide framework to examine ambushing internationally within the context of a single event or campaign.
Whilst the present work was delimited to the case of the 2018 World Cup and the use of promotional hashtags by users, broader discourse concerning sponsors and ambushers merits further investigation. The apparent acceptance of non-sponsor marketing by users may have significant implications for future marketing strategy with respect to authenticity and authority, and thus necessitates further study. Expanding the scope of ambush sentiment research to include other events and larger samples may further inform and guide the line of inquiry. Moreover, although not examined here, it merits examining how sponsorship investment and prior impressions of official sponsors impact upon consumer sentiment.
The continued study of ambush affect may also be advanced through similar examinations of ambushing and sponsorship campaigns through the lens of attitude-towards-the-ad (Aad), a concept as yet unexplored in ambush marketing theory: significant parallels exist between Aad and sentiment analysis, thus affording ambush marketing research a potential avenue into more advanced study. The contrasting motivations identified for users including either sponsor or non-sponsor hashtags in tweets reiterate the importance of effectively engaging with consumers in online settings, and in appropriately integrating new media marketing in the brand’s broader marketing strategy (Keller, 2016). Expanding upon Meenaghan et al.’s (2013) suggestion of engagement as a central for digital sponsorship activations, social network analysis of social media discourse and promotional hashtag is a logical extension of the present research.
Furthermore, the elevated use of ambush hashtags by users seeking to share campaigns both with individual followers and more broadly to act as influencers reinforces the value of social media users and successful digital marketing campaigns in driving eWOM. Although social media influencers as found on Instagram and other platforms were not identified or examined here, the role of individuals in brand sharing and sentiment creation merits further research.
This research offers new insight into consumer impressions and attitudes towards ambush marketing and sponsorship messaging online, removed from the common affect and moral heuristics applied to ambush research. The use of sentiment analysis in studying sponsorship and ambush marketing attitudes presents a viable and potentially valuable opportunity for scholars and practitioners. Consumer opposition to ambush marketing practices would appear to have been greatly overstated by rights holders in an effort to protect corporate partners: the positive sentiment evidenced by Twitter users to the three non-sponsor campaigns studied instead suggests that consumers may appreciate ambush campaigns’ creativity and subversive nature, independent of their views of official sponsors or of ambushing as an abstract construct.
Selected brands and promotional hashtags
|Budweiser||#LightUpTheWorldCup||Beats By Dre||#MadeDefiant|
Social media user motives
|Passion||“[…] directed displays of strong affection reflecting one or a combination of love, tribalism, encouragement and praise” (Stavros et al., 2014, p. 461)|
|Hope||“[…] pronouncements centered on desirable achievements and outcomes demonstrating one or a combination of ambition, expectation and situational anticipation” (Stavros et al., 2014, p. 461)|
|Esteem||“Comments directed toward the [brand] and/or fellow fans that share positive or negative personal fandom experiences, or proclaim expertise and knowledge” (Stavros et al., 2014, p. 461)|
|Camaraderie||“Community-directed comments that reflect a desire for identification within the community, including knowledge seeking and preserving the group from negative influences” (Stavros et al., 2014, p. 461)|
|Influence (adapted from Fay and Larkin, 2017)||“Comments and conversation directed towards the sharing, promotion, and discussion of branded content”|
|Commentary||“Posts reflective of individual punditry and match-commentary, scores, and news pre-, during, and post-match”|
Sentiment analysis results
|Tweet valence frequency||Ambush||Sponsor|
|Individual campaign valence|
|Coca-Cola (#ReadyFor)||0.26||Umbro (#EnglandAnthem)||0.77|
|Budweiser (#LightUpTheWorldCup)||0.07||Beats By Dre (#MadeDefiant)||0.37|
|Visa (#PayLikeZlatan)||0.08||Irn-Bru (#BruPlane)||0.81|
Comparative valence to user motivation
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