Topics, Events, Stories in Social Media
| dc.contributor.author | Hua, Ting | en |
| dc.contributor.committeechair | Lu, Chang-Tien | en |
| dc.contributor.committeemember | Reddy, Chandan K. | en |
| dc.contributor.committeemember | Li, Zhenhui | en |
| dc.contributor.committeemember | Chen, Ing-Ray | en |
| dc.contributor.committeemember | Ramakrishnan, Naren | en |
| dc.contributor.department | Computer Science | en |
| dc.date.accessioned | 2018-02-06T09:00:50Z | en |
| dc.date.available | 2018-02-06T09:00:50Z | en |
| dc.date.issued | 2018-02-05 | en |
| dc.description.abstract | The rise of big data, especially social media data (e.g., Twitter, Facebook, Youtube), gives new opportunities to the understanding of human behavior. Consequently, novel computing methods for mining patterns in social media data are therefore desired. Through applying these approaches, it has become possible to aggregate public available data to capture triggers underlying events, detect on-going trends, and forecast future happenings. This thesis focuses on developing methods for social media analysis. Specifically, five directions are proposed here: 1) semi-supervised detection for targeted-domain events, 2) topical interaction study among multiple datasets, 3) discriminative learning about the identifications for common and distinctive topics, 4) epidemics modeling for flu forecasting with simulation via signals from social media data, 5) storyline generation for massive unorganized documents. | en |
| dc.description.degree | Ph. D. | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:14018 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/82029 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Social media | en |
| dc.subject | Topic modeling | en |
| dc.subject | Event Detection | en |
| dc.title | Topics, Events, Stories in Social Media | en |
| dc.type | Dissertation | en |
| thesis.degree.discipline | Computer Science and Applications | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | doctoral | en |
| thesis.degree.name | Ph. D. | en |