Social media analysis during political turbulence
| Autor: | Polyvios Pratikakis, Despoina Antonakaki, Sotiris Ioannidis, Paraskevi Fragopoulou, Dimitris Spiliotopoulos, Christos V. Samaras |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Topic model
Emotions Social Sciences lcsh:Medicine 02 engineering and technology Elections Social Networking Sociology Referendum 0202 electrical engineering electronic engineering information engineering Psychology lcsh:Science Language media_common Multidisciplinary Greece Politics Social Communication Legislature 16. Peace & justice Linguistics Semantics Europe Greek language Social Networks 020201 artificial intelligence & image processing Network Analysis Research Article Computer and Information Sciences Political Science media_common.quotation_subject 020204 information systems Political science Humans Social media Lexicons Internet Sarcasm Information Dissemination Sentiment analysis lcsh:R Cognitive Psychology Biology and Life Sciences Communications Cognitive Science lcsh:Q Social Media Neuroscience |
| Zdroj: | PLoS ONE, Vol 12, Iss 10, p e0186836 (2017) PLOS ONE PLoS ONE |
| ISSN: | 1932-6203 |
| Popis: | Today, a considerable proportion of the public political discourse on nationwide elections proceeds in Online Social Networks. Through analyzing this content, we can discover the major themes that prevailed during the discussion, investigate the temporal variation of positive and negative sentiment and examine the semantic proximity of these themes. According to existing studies, the results of similar tasks are heavily dependent on the quality and completeness of dictionaries for linguistic preprocessing, entity discovery and sentiment analysis. Additionally, noise reduction is achieved with methods for sarcasm detection and correction. Here we report on the application of these methods on the complete corpus of tweets regarding two local electoral events of worldwide impact: the Greek referendum of 2015 and the subsequent legislative elections. To this end, we compiled novel dictionaries for sentiment and entity detection for the Greek language tailored to these events. We subsequently performed volume analysis, sentiment analysis, sarcasm correction and topic modeling. Results showed that there was a strong anti-austerity sentiment accompanied with a critical view on European and Greek political actions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|