Social media analysis during political turbulence.

Clicks: 312
ID: 79636
2017
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Abstract
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.
Reference Key
antonakaki2017socialplos Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Antonakaki, Despoina;Spiliotopoulos, Dimitris;V Samaras, Christos;Pratikakis, Polyvios;Ioannidis, Sotiris;Fragopoulou, Paraskevi;
Journal PloS one
Year 2017
DOI
10.1371/journal.pone.0186836
URL
http://europepmc.org/articles/PMC5663401?pdf=render
Keywords
adhd social interaction sarcasm social deficits tasit

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