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Social Media Influence Mainstream Media: Evidence from Two Billion Tweets

Author

Listed:
  • Julia Cagé

    (ECON - Département d'économie (Sciences Po) - Sciences Po - Sciences Po - CNRS - Centre National de la Recherche Scientifique, CEPR - Center for Economic Policy Research - CEPR)

  • Nicolas Hervé

    (INA - Institut National de l'Audiovisuel)

  • Béatrice Mazoyer

    (INA - Institut National de l'Audiovisuel, médialab - médialab (Sciences Po) - Sciences Po - Sciences Po)

Abstract

Social media are increasingly influencing society and politics, despite the fact that legacy media remain the most consumed source of news. In this paper, we study the propagation of information from social media to mainstream media, and investigate whether news editors' editorial decisions are influenced by the popularity of news stories on social media. To do so, we build a novel dataset including around 70% of all the tweets produced in French between August 2018 and July 2019 and the content published online by 200 mainstream media outlets. We then develop novel algorithms to identify and link events on social and mainstream media. To isolate the causal impact of popularity, we rely on the structure of the Twitter network and propose a new instrument based on the interaction between measures of user centrality and "social media news pressure" at the time of the event. We show that the social media popularity of a story increases the coverage of the same story by mainstream media. This effect varies depending on the media outlets' characteristics, in particular on whether they use a paywall. Finally, we investigate consumers' reaction to a surge in social media popularity. Our findings shed new light on news production decisions in the digital age and the welfare effects of social media.

Suggested Citation

  • Julia Cagé & Nicolas Hervé & Béatrice Mazoyer, 2022. "Social Media Influence Mainstream Media: Evidence from Two Billion Tweets," Working Papers hal-03877907, HAL.
  • Handle: RePEc:hal:wpaper:hal-03877907
    Note: View the original document on HAL open archive server: https://sciencespo.hal.science/hal-03877907
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    Keywords

    Internet; Information spreading; News editors; Network analysis; Social media; Twitter; Text analysis;
    All these keywords.

    JEL classification:

    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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