Predictive Analytics on Emotional Data Mined from Digital Social Networks with a Focus on Financial Markets

This dissertation is a cumulative dissertation and is comprised of five articles. User-Generated Content (UGC) comprises a substantial part of communication via social media. In this dissertation, UGC that carries and facilitates the exchange of emotions is referred to as “emotional data.” People “produce” emotional data, that is, they express their emotions via tweets, forum posts, blogs, and so on, or they “consume” it by being influenced by expressed sentiments, feelings, opinions, and the like. Decisions often depend on shared emotions and data – which again lead to new data because decisions may change behaviors or results. “Emotional Data Intelligence” ultimately seeks an answer to the question of how all the different emotions expressed in public online sources influence decision-making processes. The overarching research topic of this dissertation follows the question whether network structures and emotional sentiment data extracted from digital social networks contain predictive information or they are just noise. Underlying data was collected from different social media sources, such as Twitter, blogs, message boards, or online news and social networking sites, such as Xing. By means of methodologies of social network analysis (SNA), sentiment analysis, and predictive analysis the individual contributions of this dissertation study whether sentiment data from social media or online social networking structures can predict real-world behaviors. The focus lies on the analysis of emotional data and network structures and its predictive power for financial markets. With the formal construction of the data analyses methodologies introduced in the individual contributions this dissertation contributes to the theories of social network analysis, sentiment analysis, and predictive analytics

Early Prediction of Movie Box Office Success based on Wikipedia Activity Big Data

Use of socially generated "big data" to access information about collective states of the minds in human societies has become a new paradigm in the emerging field of computational social science. A natural application of this would be the prediction of the society's reaction to a new product in the sense of popularity and adoption rate. However, bridging the gap between "real time monitoring" and "early predicting" remains a big challenge. Here we report on an endeavor to build a minimalistic predictive model for the financial success of movies based on collective activity data of online users. We show that the popularity of a movie can be predicted much before its release by measuring and analyzing the activity level of editors and viewers of the corresponding entry to the movie in Wikipedia, the well-known online encyclopedia.Comment: 13 pages, Including Supporting Information, 7 Figures, Download the dataset from: http://wwm.phy.bme.hu/SupplementaryDataS1.zi

Does Twitter matter? The impact of microblogging word of mouth on consumers’ adoption of new movies

This research provides an empirical test of the “Twitter effect,” which postulates that microblogging word of mouth (MWOM) shared through Twitter and similar services affects early product adoption behaviors by immediately disseminating consumers’ post-purchase quality evaluations. This is a potentially crucial factor for the success of experiential media products and other products whose distribution strategy relies on a hyped release. Studying the four million MWOM messages sent via Twitter concerning 105 movies on their respective opening weekends, the authors find support for the Twitter effect and report evidence of a negativity bias. In a follow-up incident study of 600 Twitter users who decided not to see a movie based on negative MWOM, the authors shed additional light on the Twitter effect by investigating how consumers use MWOM information in their decision-making processes and describing MWOM’s defining characteristics. They use these insights to position MWOM in the word-of-mouth landscape, to identify future word-of-mouth research opportunities based on this conceptual positioning, and to develop managerial implications

Does Chatter Matter? The Impact of User-Generated Content on Music Sales

The Internet has enabled the era of user-generated content, potentially breaking the hegemony of traditional content generators as the primary sources of “legitimate” information. Prime examples of user-generated content are blogs and social networking sites, which allow easy publishing of and access to information. In this study, we examine the usefulness of such content, consisting of data from blogs and social networking sites in predicting sales in the music industry. We track the changes in online chatter for a sample of 108 albums for four weeks before and after their release dates. We use linear and nonlinear regression to identify the relative significance of online variables on their observation date in predicting future album unit sales two weeks ahead Our findings are as follows: (a) the volume of blog posts about an album is positively correlated with future sales, (b) greater increases in an artist’s Myspace friends week over week have a weaker correlation to higher future sales, (c) traditional factors are still relevant – albums released by major labels and albums with a number of reviews from mainstream sources like Rolling Stone also tended to have higher future sales. More generally, the study provides some preliminary answers for marketing managers interested in assessing the relative importance of the burgeoning number of “Web 2.0” information metrics that are becoming available on the Internet, and how looking at interactions among them could provide predictive value beyond viewing them in isolation. The study also provides a framework for thinking about when user-generated content influences decision making

Conceptualizing the Electronic Word-of-Mouth Process: What We Know and Need to Know About eWOM Creation, Exposure, and Evaluation

Electronic word of mouth (eWOM) is a prevalent consumer practice that has undeniable effects on the company bottom line, yet it remains an over-labeled and under-theorized concept. Thus, marketers could benefit from a practical, science-based roadmap to maximize its business value. Building on the consumer motivation–opportunity–ability framework, this study conceptualizes three distinct stages in the eWOM process: eWOM creation, eWOM exposure, and eWOM evaluation. For each stage, we adopt a dual lens—from the perspective of the consumer (who sends and receives eWOM) and that of the marketer (who amplifies and manages eWOM for business results)—to synthesize key research insights and propose a research agenda based on a multidisciplinary systematic review of 1050 academic publications on eWOM published between 1996 and 2019. We conclude with a discussion of the future of eWOM research and practice

Do Customers Speak Their Minds? Using Forums and Search for Predicting Sales

A wide body of research uses data from social media websites to predict offline economic outcomes such as sales. However, in practice, such data are costly to collect and process. Additionally, sales forecasts based on social media data may be hampered by people’s tendency to restrict the topics they publicly discuss. Recently, a new source of predictive information—search engine logs—has become available. Interestingly, the relationship between these two important data sources has not been studied. Specifically, do they contain complementary information? Or does the information conveyed by one source render the information conveyed by the other source redundant? This study uses Google’s comprehensive index of internet discussion forums, in addition to Google search trend data. Predictive models based on search trend data are shown to outperform and complement forum-data-based models. Furthermore, the two sources display substantially different patterns of predictive capacity over time

Sex in the city: the rise of soft-erotic film culture in Cinema Leopold, Ghent, 1945-1954

Since the 1990s, film studies saw a disciplinary shift from approaches favoring a textual and ideological analysis of films to a broader understanding of the socio-cultural history of cinema under the banner of new cinema history. This turn not only allowed for ‘niche’ research domains to flourish such as film economics or cinema memory research, or for new empirical and critical methodologies to be applied to film and cinema history. This change in researching and writing film/cinema history also shed light on previously marginalized, neglected or uncharted film cultures and histories, burgeoning scholarship in for instance (s)exploitation cinema. This contribution examines a peculiar part of post-war local film culture in the Belgian city of Ghent, more precisely the one around the city-center soft-erotic cinema Cinema Leopold (1945-54). The research is based on a programming and box-office database compiled from archival sources and contextualized by other data (internal and external correspondence, posters,…) coming from the business archive of Octave Bonnevalle, Cinema Leopold’s founding pater familias (material kept in the State Archives of Belgium; RAB/B70/1928-1977). The database now contains information on 625 film titles shown between 1945 and 1954, out of which 233 were unidentified (due to lack of information). Although the database is at times crippled by source inconsistencies, it is extremely rich in documenting the everyday practices of a cinema that gradually turned into a soft-erotic movie theater. The database allows for some remarkable findings concerning shifts in the origin of films, their production years, genres, censorship and popularity. The key finding is that Cinema Leopold started out after the Second World War with a child-friendly, mainstream Hollywood-oriented film program, as did most cinemas in Ghent, but its profile slowly tilted towards more mature audiences and provocative film genres. These included French ‘risqué’ feature films containing some forms of nudity like Perfectionist/Un Grand Patron (Ciampi, 1951) and documentaries on venereal diseases like the successful Austrian Creeping Poison/Schleichendes Gift (Wallbrück, 1946), but also auteur movies such as Bergman’s Port of Call/Hamnstad (1948) were shown. It is interesting how Leopold walked a fine line between innovative, bold European art-house cinema, soft-erotic ‘didactic’ movies and flat-out commercial soft-porn. By 1954, Leopold had gathered a loyal crowd, which kept the cinema alive until 1981 despite the several law suits and trials. This micro-history offers a remarkable example of the post-war flourishing of alternative, yet profit-driven cinema circuits, riddled with media controversies and censorship