Weakly Supervised Learning for Analyzing Political Campaigns on Facebook
- URL: http://arxiv.org/abs/2210.10669v2
- Date: Tue, 9 May 2023 13:13:47 GMT
- Title: Weakly Supervised Learning for Analyzing Political Campaigns on Facebook
- Authors: Tunazzina Islam, Shamik Roy, Dan Goldwasser
- Abstract summary: We propose a weakly supervised approach to identify the stance and issue of political ads on Facebook.
We analyze the temporal dynamics of the political ads on election polls.
- Score: 24.29993132301275
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: Social media platforms are currently the main channel for political
messaging, allowing politicians to target specific demographics and adapt based
on their reactions. However, making this communication transparent is
challenging, as the messaging is tightly coupled with its intended audience and
often echoed by multiple stakeholders interested in advancing specific
policies. Our goal in this paper is to take a first step towards understanding
these highly decentralized settings. We propose a weakly supervised approach to
identify the stance and issue of political ads on Facebook and analyze how
political campaigns use some kind of demographic targeting by location, gender,
or age. Furthermore, we analyze the temporal dynamics of the political ads on
election polls.
Related papers
- On the Use of Proxies in Political Ad Targeting [49.61009579554272]
We show that major political advertisers circumvented mitigations by targeting proxy attributes.
Our findings have crucial implications for the ongoing discussion on the regulation of political advertising.
arXiv Detail & Related papers (2024-10-18T17:15:13Z) - Whose Side Are You On? Investigating the Political Stance of Large Language Models [56.883423489203786]
We investigate the political orientation of Large Language Models (LLMs) across a spectrum of eight polarizing topics.
Our investigation delves into the political alignment of LLMs across a spectrum of eight polarizing topics, spanning from abortion to LGBTQ issues.
The findings suggest that users should be mindful when crafting queries, and exercise caution in selecting neutral prompt language.
arXiv Detail & Related papers (2024-03-15T04:02:24Z) - 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) - Political advertisement on Facebook and Instagram in the run up to 2022
Italian general election [0.9496529663479973]
We study the extent to which political ads were delivered on Facebook and Instagram in the run up to 2022 Italian general election.
We analyze over 23 k unique ads paid by 2.7 k unique sponsors, with an associated amount spent of 4 M EUR and over 1 billion views generated.
We find results that are in accordance with their political agenda and the electoral outcome.
arXiv Detail & Related papers (2022-12-12T13:37:18Z) - The impact of Twitter on political influence on the choice of a running
mate: Social Network Analysis and Semantic Analysis -- A Review [0.0]
Politics is one of the most talked-about and popular topics on social media networks right now.
Many politicians use micro-blogging services like Twitter because they have a large number of followers and supporters on those networks.
This research is a review on the use of social network analysis (SNA) and semantic analysis (SA) on the Twitter platform to study the supporters networks of political leaders.
arXiv Detail & Related papers (2022-07-31T17:44:57Z) - How Algorithms Shape the Distribution of Political Advertising: Case
Studies of Facebook, Google, and TikTok [5.851101657703105]
We analyze a dataset containing over 800,000 ads and 2.5 million videos about the 2020 U.S. presidential election from Facebook, Google, and TikTok.
We conduct the first large scale data analysis of public data to critically evaluate how these platforms amplified or moderated the distribution of political advertisements.
We conclude with recommendations for how to improve the disclosures so that the public can hold the platforms and political advertisers accountable.
arXiv Detail & Related papers (2022-06-09T18:19:30Z) - 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) - 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) - Analyzing Online Political Advertisements [10.386018392170083]
We present the first computational study on online political ads with the aim to infer the political ideology of an ad sponsor.
We develop two new large datasets for the two tasks consisting of ads from the U.S.
arXiv Detail & Related papers (2021-05-09T23:18:37Z) - Political Posters Identification with Appearance-Text Fusion [49.55696202606098]
We propose a method that efficiently utilizes appearance features and text vectors to accurately classify political posters.
The majority of this work focuses on political posters that are designed to serve as a promotion of a certain political event.
arXiv Detail & Related papers (2020-12-19T16:14:51Z)
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.