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Contribution Details
| Type | Bachelor's Thesis |
| Scope | Discipline-based scholarship |
| Title | Tweet Sentiment and Earnings Announcements |
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| Institution | University of Zurich |
| Faculty | Faculty of Economics, Business Administration and Information Technology |
| Number of Pages | 32 |
| Date | 2015 |
| Abstract Text | Advancements in technology have enabled internet users not only to view stock price movements in real-time, but also to comment on them publicly through various outlets. One such outlet is the microblogging platform Twitter with over 288 million monthly active users (Twitter (2015a)). Modern computational linguistics offer the opportunity to classify text sentiment of such comments. Hence this study takes advantage of linguisitc text classification for the purpose of analyzing people’s positivity before and after earnings announcements, in order to expose relationships between the tone of earnings announcements, earnings surprise, stock market reaction and twitter sentiment in this particular context. |
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