RESEARCH

"Online and Offline protest participation: An Empirical Analysis for the 2020 Black Lives Matter Movement" Abstract
The recent wave of world-wide protests that took place after George Floyd’s killing has sparked attention in the Black Lives Matter movement, specially in terms of online activism. How does offline protesting behavior interact with the underlying online social networks? In this work, I build a classification algorithm to identify individuals who physically participated in the BLM denmostrations across US. Thanks to this unique dataset, I explore at a individual level their full Twitter activity to better understand the role of influencial users, coordination patterns and speech evolution. Through this analysis, I aim to examine assumptions regarding slacktivism, which involves engaging in online activism with minimal effort, in comparison to more traditional forms of protesting. By exploring how social media contributes to the development of traditional activism, we can gain a deeper understanding of the role of social media in protesting behavior.

"Breaking the Echo Chamber: Nonviolent Protest and Police Violence on Twitter" with Hannes Mueller, Daniel Montolio and Francesco Slataper. Abstract
Social media platforms play a crucial role in shaping public discourse and political conflict. But political conflict also shapes social media networks. This paper investi- gates the response of social media networks to conflict events during the height of the independence struggle in 2017 in Catalonia (Spain). The analysis exploits linguistic markers to study retweets across Catalan and Castellano language groups in a large Twitter/X corpus of 65 million tweets during this conflict. To study behavioral changes, the article proposes a statistical decomposition into ‘exposure’—the likelihood of en- countering specific content—and ‘retweet rates’—the probability of retweeting content once exposed. Surprisingly, the conflict events were associated with a dramatic relative increase in retweet rates across language groups. There is evidence of an ideological realignment, where left-wing voters in both language groups retweeted each other more frequently.

"The Impact of Political Campaigns on Demand for Partisan News" Abstract
How do people acquire political information during political campaigns? Using a unique dataset that comprises both audience data and text content from Spanish TV news, we estimate the demand for political information. We rely on Large Language Models to categorize the tone associated with each political party in each story of the day. To address endogeneity concerns regarding the political leaning of the content offered, we use input shocks that constrain channels' political news production asymmetrically. While outlets strive to maintain their political stance, these shocks affect them differently, depending on the day's random news composition. Our findings show that the demand for political information decreases during political campaigns. Moreover, campaigns trigger a polarized news consumption, with right-leaning viewers demanding more favorable content on their own party and more negative coverage of the opposing parties.

TEACHING

• Teaching Assistant:
  • Introduction to Text Mining and Natural Language Processing -- Data Science for Decision Making Program, BSE
  • Econometrics I -- IDEA Master Programme, UAB
  • Microeconomics I -- IDEA Master Programme, UAB
  • Master Thesis -- EPP Master Programme, BSE
• Others:
  • Brush up- Introduction to Python Programming -- Data Science for Decision Making Program, BSE

CONTACT

Institut d'Anàlisi Econòmica. 08193 Bellaterra. Office 126
Email: luisigmenendez@gmail.com

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