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How do sentiments affect virality on Twitter?

Salud María Jiménez-Zafra1, Antonio José Sáez-Castillo2, Antonio Conde-Sánchez2

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Researchers studied Twitter virality and found that negative sentiment in tweets increases retweeting probability. The iSOL lexicon best explains the link between sentiment polarity and tweet spread.

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Area of Science:

  • Social Media Analysis
  • Computational Linguistics
  • Political Communication

Background:

  • Twitter virality is a growing research area.
  • Understanding factors influencing retweets is crucial for analyzing information spread.
  • The Spanish political context, specifically the 2017 Catalan referendum, provides a relevant case study.

Purpose of the Study:

  • To investigate the impact of sentiment expression on tweet retweeting frequencies.
  • To identify linguistic factors that correlate with Twitter virality.
  • To analyze sentiment polarity's effect on the spread of political information.

Main Methods:

  • Utilized a regression model to analyze the number of retweets.
  • Focused on tweets related to the 2017 Catalan pseudo-referendum.
  • Employed sentiment analysis, specifically using the iSOL lexicon.

Main Results:

  • The use of negative sentiment in tweets was found to increase the probability of retweeting.
  • The iSOL lexicon demonstrated a strong correlation between sentiment polarity and virality.
  • Tweet negativity emerged as a significant predictor of retweet frequency.

Conclusions:

  • Negative sentiment plays a key role in driving Twitter virality, particularly in political contexts.
  • The iSOL lexicon is effective in quantifying the relationship between sentiment and retweeting behavior.
  • Findings offer insights into the dynamics of online information dissemination and political discourse.