| Publication Type |
dissertation |
| School or College |
David Eccles School of Business |
| Department |
Entrepreneurship & Strategy |
| Author |
Oh, Chong Keat |
| Title |
Peer influence, information quality and predictive power of stock microblogs |
| Date |
2013-05 |
| Description |
Due to the popularity of Web 2.0 and Social Media in the last decade, the percolation of user generated content (UGC) has rapidly increased. In the financial realm, this results in the emergence of virtual investing communities (VIC) to the investing public. There is an on-going debate among scholars and practitioners on whether such UGC contain valuable investing information or mainly noise. I investigate two major studies in my dissertation. First I examine the relationship between peer influence and information quality in the context of individual characteristics in stock microblogging. Surprisingly, I discover that the set of individual characteristics that relate to peer influence is not synonymous with those that relate to high information quality. In relating to information quality, influentials who are frequently mentioned by peers due to their name value are likely to possess higher information quality while those who are better at diffusing information via retweets are likely to associate with lower information quality. Second I propose a study to explore predictability of stock microblog dimensions and features over stock price directional movements using data mining classification techniques. I find that author-ticker-day dimension produces the highest predictive accuracy inferring that this dimension is able to capture both relevant author and ticker information as compared to author-day and ticker-day. In addition to these two studies, I also explore two topics: network structure of co-tweeted tickers and sentiment annotation via crowdsourcing. I do this in order to understand and uncover new features as well as new outcome indicators with the objective of improving predictive accuracy of the classification or saliency of the explanatory models. My dissertation work extends the frontier in understanding the relationship between financial UGC, specifically stock microblogging with relevant phenomena as well as predictive outcomes. |
| Type |
Text |
| Publisher |
University of Utah |
| Subject |
Information quality; Peer influence; Predictive analytics; Stock microblogging; Virtual investing communities |
| Dissertation Institution |
University of Utah |
| Dissertation Name |
Doctor of Philosophy |
| Language |
eng |
| Rights Management |
Copyright © Chong Keat Oh 2013 |
| Format Medium |
application/pdf |
| Format Extent |
1,942,251 Bytes |
| Identifier |
etd3/id/3468 |
| ARK |
ark:/87278/s69w3prj |
| Setname |
ir_etd |
| ID |
197022 |
| Reference URL |
https://collections.lib.utah.edu/ark:/87278/s69w3prj |
