Influence of Ecuadorian Homosexual Subculture in Consumption Culture: Study about Information Consumption on Twitter

Abstract

This qualitative research examines the Ecuadorian homosexual subculture and determines how gender, images, texts, and objects are referred to consumption culture. The netnography method was used to collect data from Twitter conversations. Categorization and classification of the conversations showed how the information was created, the purpose of the message, and the target audience. Results reveal common subjects in relation to news, human rights, and gender equality. Subjects were conceptualized based on the consumption of information in social, cultural, and political environments. It was concluded that images, texts, and objects included in the conversations provide significant information about the homosexual subculture consumption behavior.     

Following brands on Twitter: an extension of theory of planned behavior

Due to its immediacy and efficiency, Twitter has recently emerged as a form of marketing communication tool that offers unique advantages for two-way communication between marketers and consumers. This study examines brand-following behavior on Twitter using the Ajzen's model of theory of planned behavior (TPB). Results show that attitude toward brand following, subjective norm, perceived behavioral control, and brand attachment are positively associated with intention to follow brands on Twitter. Consumers’ intention to create (i.e., intention to tweet at brands) and disseminate (i.e., intention to retweet the links of brands) brand-related information, as well as purchase intention, are the outcomes of intention to follow brands on Twitter. Overall findings suggest that TPB model can be used to predict Twitter users’ brand-following behavior. More importantly, our finding that brand attachment drives consumer intention to follow brands on Twitter extends the TPB framework. This study provides both theoretical and managerial implications.     

Social media? Get serious! Understanding the functional building blocks of social media

Traditionally, consumers used the Internet to simply expend content: they read it, they watched it, and they used it to buy products and services. Increasingly, however, consumers are utilizing platforms—such as content sharing sites, blogs, social networking, and wikis—to create, modify, share, and discuss Internet content. This represents the social media phenomenon, which can now significantly impact a firm's reputation, sales, and even survival. Yet, many executives eschew or ignore this form of media because they don’t understand what it is, the various forms it can take, and how to engage with it and learn. In response, we present a framework that defines social media by using seven functional building blocks: identity, conversations, sharing, presence, relationships, reputation, and groups. As different social media activities are defined by the extent to which they focus on some or all of these blocks, we explain the implications that each block can have for how firms should engage with social media. To conclude, we present a number of recommendations regarding how firms should develop strategies for monitoring, understanding, and responding to different social media activities.     

The interaction effect of emoji and social media content on consumer engagement: A mixed approach on peer-to-peer accommodation brands

This study examines how the interaction between emoji (emotional vs semantic) and social media content (aesthetic experience vs promotion) influences consumer engagement in tourism brands' digital communication. Based on real Twitter data and an online experiment, our results show that, for aesthetic experience content, emotional emoji elicits more consumer engagement than semantic emoji does. Moreover, emotional emoji increases consumer engagement by eliciting a higher level of emotional responses for aesthetic experience content, whereas semantic emoji enhances consumer engagement by generating greater credibility for promotion content. This study contributes to the textual paralanguage literature in tourism by offering theoretical explanations on how and why the matching effects of emoji and content type on consumer engagement occur in tourism brands’ digital communication. This study also provides practical implications for tourism social media marketers on how to increase consumer engagement via the appropriate use of emoji.     

eWOM across channels: comparing the impact of self-enhancement,positivity bias and vengeance on Facebook and Twitter

Abstract

When sharing personal details, versus talking about others, consumers tend to accentuate the positive experiences they have with brands in order to self-enhance amongst friends. Consumers also take vengeance on brands in public venues. Turning to social network sites (SNSs), it is unclear which is dominant. Here historical Facebook and Twitter eWOM (n = 47,907) is analyzed for a static group of 783 active US consumers. Self-enhancement is found on both SNSs. The majority of eWOM is positive Vengeance was rare, occurring only in 10.3% of all eWOM. eWOM appears to mirror a consumer's non-eWOM sentiment valence across SNSs. In this cross-platform comparison we suggest that SNS affordances alter eWOM creation Facebook has privacy expectations and limits direct brand interactions. Twitter is a public platform with less privacy expectations and a larger customer service component. Here eWOM is more prevalent on Twitter but contrary to our expectations is more positive.     

Happiness sentiments and the prediction of cross-border country exchange-traded fund returns

This research examines whether social media (Twitter) happiness sentiment and country-level happiness sentiment indices predict cross-border ETF returns. To account for complicated associations between happiness sentiment and ETF returns, we use a quantile regression approach and find that Twitter and trading market (U.S.) happiness sentiments are strong predictors of future ETF returns, for which both have far greater predictive power than those of their home countries. Home country happiness indices exhibit asymmetric impacts across quantiles, suggesting the importance of trading country (U.S.) and Twitter happiness sentiments. Higher U.S. and home countries’ freedom to make life choices, absence of corruption perception, and confidence in national government precede higher ETF returns, while U.S. GDP, social support, health life expectancy, positive affect, and negative affect precede lower (abnormal) returns. We find that higher return quantile country ETFs provide a safe haven for U.S. investors during a U.S. bear market.     

The Cinderella moment: Exploring consumers' motivations to engage with renting as collaborative luxury consumption mode

Past literature argued that the purchase of luxury goods is driven by people's motivation to conform or fit into our economic and social system. In this study, the authors focus on a new aspect of consumption, that is, renting instead of purchasing luxury goods, backed by the emerging opportunities of sharing economy platforms. Drawing upon the analysis of spontaneous consumers' online communications (in the form of tweets), this study aims to investigate the motivations to engage with luxury garment renting within a collaborative consumption context. To this end, a series of automatic content analyses, via two studies, were conducted using the tweets posted with respect to the Run the Runway collaborative consumption platform. Results demonstrate consumers' increased willingness to show their social status through renting rather than owning luxurious apparel based on five main motivators (need to wear new clothes for a special event, inspirations created by the products/brands, possibility to explore a new way of consuming luxury goods, need to make more sustainable choices, and to increase the life cycle of each luxury product). The implications of these findings are discussed, while they pave the way for future research in collaborative consumption of luxury retailing.     

Does Twitter chatter matter? Online reviews and box office revenues

ABSTRACT

With a rapid rise of text-based social media and online Word-of-Mouth (WOM) activity, millions of people express their thoughts and opinions on a variety of topics. Considering that nowadays WOM is a most influential source of information when guiding consumers’ choice and purchase decisions, in this paper we look at the relationship between Twitter messages (tweets) and cinema box office revenues. Using static and dynamic panel data regression approaches, we show that the frequency, sentiment and timing of tweets posted about a film are correlated to different extent with the movie’s box office revenues, with negative tweets being particularly damaging to the box office revenues. From a managerial perspective, this is important to know, such that film production companies and distributors can adjust their strategy accordingly.     

From Returns to Tweets and Back: An Investigation of the Stocks in the Dow Jones Industrial Average

A sizeable percentage of investors are using social media to obtain information about companies (Cogent Research [2008]). As a consequence, social media content about firms may have an impact on stock prices (Hachman [2011]). Various studies utilize social media content to forecast stock market-related factors such as returns, volatility, or trading volume. The objective of this article is to investigate whether a bidirectional intraday relationship between stock returns and volatility and tweets exists. The study analyzed 150,180 minute-by-minute stock price and tweet data for the 30 stocks in the Dow Jones Industrial Average over a random 13-day interval from June 2 to June 18, 2014 using a BEKK-MVGARCH methodology. Findings indicate that 87% of stock returns are influenced by lagged innovations of the tweets data, but there is little evidence to support that the direction is reciprocal, with only 7% of tweets being influenced by lagged innovations of the stock returns. Results further show that the lagged innovations from 40 percent of stock returns affect the current conditional volatility of the tweets, while 73 percent of tweets affect the current conditional volatility of stock returns. Moreover, there is strong evidence to suggest that the volatility originating from the returns to the tweets persists for 33 percent of stocks; the volatility originating from the tweets to the returns persists for 73 percent of stocks. Last, 53 percent of stocks exhibit both immediate and persistent impacts from returns to tweets, while 90 percent of stocks exhibit both immediate and persistent impacts from tweets to returns. These results may help traders achieve superior returns by buying and selling individual stocks or options. Also, asset and mutual fund managers may benefit by developing a social media strategy.