Analyzing political stances on Twitter in the lead-up to the 2024 U.S. election
- URL: http://arxiv.org/abs/2412.02712v1
- Date: Thu, 28 Nov 2024 07:05:34 GMT
- Title: Analyzing political stances on Twitter in the lead-up to the 2024 U.S. election
- Authors: Hazem Ibrahim, Farhan Khan, Hend Alabdouli, Maryam Almatrooshi, Tran Nguyen, Talal Rahwan, Yasir Zaki,
- Abstract summary: We investigate the ideological positioning of tweets related to the 2024 U.S. Presidential Election.
We classify ideological stances into Pro-Democrat, Anti-Republican, Pro-Republican, Anti-Democrat, and Neutral categories.
We find that Republican candidates author significantly more tweets in criticism of the Democratic party and its candidates than vice versa.
- Score: 1.2764774886497106
- License:
- Abstract: Social media platforms play a pivotal role in shaping public opinion and amplifying political discourse, particularly during elections. However, the same dynamics that foster democratic engagement can also exacerbate polarization. To better understand these challenges, here, we investigate the ideological positioning of tweets related to the 2024 U.S. Presidential Election. To this end, we analyze 1,235 tweets from key political figures and 63,322 replies, and classify ideological stances into Pro-Democrat, Anti-Republican, Pro-Republican, Anti-Democrat, and Neutral categories. Using a classification pipeline involving three large language models (LLMs)-GPT-4o, Gemini-Pro, and Claude-Opus-and validated by human annotators, we explore how ideological alignment varies between candidates and constituents. We find that Republican candidates author significantly more tweets in criticism of the Democratic party and its candidates than vice versa, but this relationship does not hold for replies to candidate tweets. Furthermore, we highlight shifts in public discourse observed during key political events. By shedding light on the ideological dynamics of online political interactions, these results provide insights for policymakers and platforms seeking to address polarization and foster healthier political dialogue.
Related papers
- Finding Hidden Swing Voters in the 2022 Italian Elections Twitter Discourse [1.3654846342364308]
We examine the dynamics of political messaging and voter behavior on Twitter during the 2022 Italian general elections.
Our analysis reveals that during election periods, the popularity of politicians increases, and there is a notable variation in the use of persuasive language techniques.
Swing voters are more vulnerable to these propaganda techniques compared to non-swing voters, with differences in vulnerability patterns across various types of political shifts.
arXiv Detail & Related papers (2024-07-01T13:34:29Z) - Quantifying the Uniqueness of Donald Trump in Presidential Discourse [51.76056700705539]
This paper introduces a novel metric of uniqueness based on large language models.
We find considerable evidence that Trump's speech patterns diverge from those of all major party nominees for the presidency in recent history.
arXiv Detail & Related papers (2024-01-02T19:00:17Z) - Identity Collapse? Realignment of Taiwanese Voters in the 2024
Presidential Elections on Social Media [2.5835347022640254]
The 2024 Taiwanese Presidential Election is not just a critical geopolitical event, it also engages with long-standing debate in politics.
We analyze user (predominantly Taiwanese) discourse and engagement along the axes of national identity, issue topic, and partisan alignment.
We discuss how the dissolution of Taiwan's single-issue society may not just lead to more viable candidates and multi-issue discourse, but the misalignment of national and partisan identity may heal deep-seated partisan cleavages.
arXiv Detail & Related papers (2023-10-10T17:52:27Z) - Social media polarization reflects shifting political alliances in
Pakistan [44.99833362998488]
Spanning from 2018 to 2022, our analysis of Twitter data allows us to capture pivotal shifts and developments in Pakistan's political arena.
By examining interactions and content generated by politicians affiliated with major political parties, we reveal a consistent and active presence of politicians on Twitter.
Our analysis also uncovers significant shifts in political affiliations, including the transition of politicians to the opposition alliance.
arXiv Detail & Related papers (2023-09-15T00:07:48Z) - Millions of Co-purchases and Reviews Reveal the Spread of Polarization
and Lifestyle Politics across Online Markets [68.8204255655161]
We study the pervasiveness of polarization and lifestyle politics over different product segments in a diverse market.
We sample 234.6 million relations among 21.8 million market entities to find product categories that are politically relevant, aligned, and polarized.
Cultural products are 4 times more polarized than any other segment.
arXiv Detail & Related papers (2022-01-17T18:16:37Z) - Demographic Confounding Causes Extreme Instances of Lifestyle Politics
on Facebook [73.37786708074361]
We find that the most extreme instances of lifestyle politics are those which are highly confounded by demographics such as race/ethnicity.
The most liberal interests included electric cars, Planned Parenthood, and liberal satire while the most conservative interests included the Republican Party and conservative commentators.
arXiv Detail & Related papers (2022-01-17T16:48:00Z) - Shifting Polarization and Twitter News Influencers between two U.S.
Presidential Elections [92.33485580547801]
We analyze the change of polarization between the 2016 and 2020 U.S. presidential elections.
Most of the top influencers were affiliated with media organizations during both elections.
75% of the top influencers in 2020 were not present in 2016, demonstrating that such status is difficult to retain.
arXiv Detail & Related papers (2021-11-03T20:08:54Z) - Reaching the bubble may not be enough: news media role in online
political polarization [58.720142291102135]
A way of reducing polarization would be by distributing cross-partisan news among individuals with distinct political orientations.
This study investigates whether this holds in the context of nationwide elections in Brazil and Canada.
arXiv Detail & Related papers (2021-09-18T11:34:04Z) - Characterizing Partisan Political Narratives about COVID-19 on Twitter [2.5599656137521425]
We characterize and compare the pandemic narratives of the Democratic and Republican politicians on social media.
By analyzing tweets from the politicians in the U.S., we uncover the contrasting narratives in terms of topics, frames, and agents.
Our findings concretely expose the gaps in the "elusive consensus" between the two parties.
arXiv Detail & Related papers (2021-03-11T21:24:41Z) - Towards Measuring Adversarial Twitter Interactions against Candidates in
the US Midterm Elections [25.374045377135307]
We measure the adversarial interactions against candidates for the US House of Representatives during the run-up to the 2018 US general election.
We develop a new technique for detecting tweets with toxic content that are directed at any specific candidate.
We use these techniques to outline the breadth of adversarial interactions seen in the election, including offensive name-calling, threats of violence, posting discrediting information, attacks on identity, and adversarial message repetition.
arXiv Detail & Related papers (2020-05-09T10:00:41Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.