Talk Bursts: The Role of Spikes in Prerelease Word-of-Mouth Dynamics

Gelper, Sarah; Peres, Renana; Eliashberg, Jehoshua

doi:10.1177/0022243718817007

Cited by 48 publications

(30 citation statements)

References 57 publications

(70 reference statements)

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“…A large-scale meta-analysis demonstrates that social media is positively correlated with sales (Rosario et al 2016). Social media activity is increasingly recognized as an important firm asset (Kumar 2018), proving to be beneficial in new product launches (Gelper, Peres, and Eliashberg 2018) and in choosing brand alliance partners (Kupfer et al 2018).…”

Section: Literature Reviewmentioning

confidence: 99%

The Influence of Global Brand Distribution on Brand Popularity on Social Media

Kim¹,

Moon²,

Iacobucci³

2019

Journal of International Marketing

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The literature on consumer choice between global and local brands is focused on sales-based measures of brand globalness (BG). When managers need to establish an effective social media campaign to raise awareness of their brands’ activities on social media, the literature focus may not provide clear guidance on how such measures can be applied to social media. This research contributes to global brand research by combining the literature streams on consumer social media engagement and global branding marketing strategies. First, to provide a managerial tool for this task, the authors propose two novel measures, BG and country brand popularity (CBP), based on consumers’ brand activities on social media. Using these measures, the authors hypothesize that CBP is influenced by cultural, social, and economic factors, which is motivated by motivation–opportunity–ability theory. Using Facebook data covering the top 100 brands that operate across 50 countries in each of 51 industries, they show that CBP is influenced by BG and cultural, social, and economic characteristics.

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Section: Literature Reviewmentioning

confidence: 99%

The Influence of Global Brand Distribution on Brand Popularity on Social Media

Kim¹,

Moon²,

Iacobucci³

2019

Journal of International Marketing

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“…From a temporal perspective, WOM often shows spikes or sudden increases in volume, which can be firm‐ or consumer‐driven (Gelper, Peres, & Eliashberg, ). WOM that occurs during spikes differs in content from that which occurs outside of spikes (e.g., it contains more positive affect), which may alter product signals and the impact of WOM.…”

Section: Platformmentioning

confidence: 99%

“…WOM that occurs during spikes differs in content from that which occurs outside of spikes (e.g., it contains more positive affect), which may alter product signals and the impact of WOM. Indeed, movies with more pre‐release spikes have higher box‐office revenues, controlling for WOM volume and valence, and for movie characteristics (Gelper et al, ).…”

Section: Platformmentioning

confidence: 99%

“…Ultimately, the effect of the marketing mix on receivers is dynamic: marketing mix variables increase sales and drive WOM (e.g., Berger & Schwartz, ; Fossen & Schweidel, ; Fossen & Schweidel, ; Kuksov & Xie, ; Lovett, Peres, & Shachar, ), which, in turn, affects product diffusion (e.g., Amblee & Bui, ; Chintagunta et al, ; Dellarocas Zhang & Awad, ; Gelper et al, ; Godes & Mayzlin, ; Park & Kim, ) and subsequent WOM (Park, Shin, & Xie, ). By monitoring WOM, sellers can assess consumers’ perceptions of product quality, changes in the importance of product attributes, and shifts in market position and competitiveness (e.g., Chen & Xie, ; Kwark, Chen, & Raghunathan, ; Netzer, Feldman, Goldenberg, & Fresko, ; Timoshenko & Hauser, ; Tirunillai & Tellis, ), and adjust the marketing mix accordingly.…”

Section: Sellermentioning

confidence: 99%

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How online word‐of‐mouth impacts receivers

Moore

Lafreniere

2019

Consumer Psychology Review

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Online word‐of‐mouth (WOM) can impact consumers’ product evaluations, purchase intentions, and choices—but when does it do so? How do those receiving WOM know whether to rely on a particular message? This article suggests that the multiple players involved in online WOM (receivers, senders, sellers, platforms, and other consumers) each have their own interests, which are often in conflict. Thus, receivers of WOM are faced with a judgment task in deciding what information to rely on: They must make inferences about the product in question and about the players who provide or present WOM. To do so, they use signals embedded in various components of WOM, such as average star ratings, message content, or sender characteristics. The product and player information provided by these signals shapes the impact of WOM by allowing receivers to make inferences about (a) their likelihood of product satisfaction, and (b) the trustworthiness of WOM players, and therefore the trustworthiness of their content. This article summarizes how each player changes the impact of online WOM, providing a lens for understanding the current literature in online WOM, offering insights for theory in this context, and opening up pathways for future research.

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“…For example, Hennig-Thurau, Wiertz, and Feldhaus (2015) examine Twitter to study the diagnostic value of microblogging WOM and find that negative tweets are potentially harmful to a movie’s early box office revenue. Gelper, Peres, and Eliashberg (2018) note that sporadic volume bursts, or spikes of online WOM prior to a movie’s release, are positively associated with opening weekend box office revenue. Recently, academics have paid increasing attention to online WOM content beyond its overall valence.…”

Section: Related Literaturementioning

confidence: 97%

Do Spoilers Really Spoil? Using Topic Modeling to Measure the Effect of Spoiler Reviews on Box Office Revenue

Ryoo

Wang

2020

Journal of Marketing

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A sizable portion of online movie reviews contain spoilers, defined as information that prematurely resolves plot uncertainty. In this research, the authors study the consequences of spoiler reviews using data on box office revenue and online word of mouth for movies released in the United States. To capture the degree of information in spoiler review text that reduces plot uncertainty, the authors propose a spoiler intensity metric and measure it using a correlated topic model. Using a dynamic panel model with movie fixed effects and instrumental variables, the authors find a significant and positive relationship between spoiler intensity and box office revenue with an elasticity of .06. The positive effect of spoiler intensity is greater for movies with a limited release, smaller advertising spending, and moderate user ratings, and is stronger in the earlier days after the movie’s release. Using an event study and online experiments, the authors provide further evidence that spoiler reviews can help consumers reduce their uncertainty about the quality of movies, consequently encouraging theater visits. Thus, movie studios may benefit from consumers’ access to plot-intense reviews and should actively monitor the content of spoiler reviews to better forecast box office performance.

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Talk Bursts: The Role of Spikes in Prerelease Word-of-Mouth Dynamics

Cited by 48 publications

References 57 publications

The Influence of Global Brand Distribution on Brand Popularity on Social Media

The Influence of Global Brand Distribution on Brand Popularity on Social Media

How online word‐of‐mouth impacts receivers

Do Spoilers Really Spoil? Using Topic Modeling to Measure the Effect of Spoiler Reviews on Box Office Revenue

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