Twitter Data for Predicting Election Results: Insights from Emotion Classification
| Autor: | Colin J. Neill, Satish M. Srinivasan, Tianhai Zu, Raghvinder S. Sangwan |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Social network
business.industry Microblogging Emotion classification media_common.quotation_subject General Engineering General Social Sciences 02 engineering and technology Variety (cybernetics) Feeling 020204 information systems 0202 electrical engineering electronic engineering information engineering medicine Happiness Anxiety Social media medicine.symptom business Psychology Social psychology media_common |
| Zdroj: | IEEE Technology and Society Magazine. 38:58-63 |
| ISSN: | 1937-416X 0278-0097 |
| Popis: | The advent of social media and microblogging sites has paved the way for individuals and communities to freely express their opinions, feelings, and thoughts on a variety of topics in the form of short and limited size texts such as tweets. These tweets can hold a wealth of information on how individuals communicate their thoughts, emotions (happiness, anxiety, depression, etc.) and feelings within their social network [1]. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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