Abstract
Social media corpora, including the textual output of blogs, forums, and messaging applications, provide fertile ground for linguistic analysis material diverse in topic and style, and at Web scale. We investigate manifest properties of textual messages, including latent topics, psycholinguistic features, and author mood, of a large corpus of blog posts, to analyze the impact of age, emotion, and social connectivity. These properties are found to be significantly different across the examined cohorts, which suggest discriminative features for a number of useful classification tasks. We build binary classifiers for old versus young bloggers, social versus solo bloggers, and happy versus sad posts with high performance. Analysis of discriminative features shows that age turns upon choice of topic, whereas sentiment orientation is evidenced by linguistic style. Good prediction is achieved for social connectivity using topic and linguistic features, leaving tagged mood a modest role in all classifications.
Original language | English |
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Title of host publication | Web Information System Engineering, WISE 2011 - 12th International Conference, Proceedings |
Pages | 227-240 |
Number of pages | 14 |
DOIs | |
Publication status | Published - 19 Oct 2011 |
Externally published | Yes |
Event | International Conference on Web Information Systems Engineering 2011 - Sydney, Australia Duration: 13 Oct 2011 → 14 Oct 2011 Conference number: 12th https://link.springer.com/book/10.1007/978-3-642-24434-6 (Proceedings) |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 6997 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | International Conference on Web Information Systems Engineering 2011 |
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Abbreviated title | WISE 2011 |
Country/Territory | Australia |
City | Sydney |
Period | 13/10/11 → 14/10/11 |
Internet address |
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