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Predicting User's Political Party Using Ideological Stances
[chapter]
2013
Lecture Notes in Computer Science
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In our work, we exploit users' ideological stances on controversial issues to predict political party of online users. ...
Several political research studies on it indicate that political parties' ideological beliefs on sociopolitical issues may influence the users political leaning. ...
We use R for our stance prediction experiments. We use users' political party information as gold truth for our party prediction experiments. ...
doi:10.1007/978-3-319-03260-3_16
fatcat:hz45hvedvjgizju73mbnuketpa
Cross-Cutting Political Awareness through Diverse News Recommendations
[article]
2019
arXiv
pre-print
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Our research on recommendation diversity and political polarization helps us to develop algorithms that measure each user's reaction %to diverse viewpoints and adjust the recommendation accordingly. ...
This limits users' exposure to diverse viewpoints and potentially increases political polarization. ...
As a next step, we are using these insights to deploy and test them in a large-scale experiment involving multiple news producers and consumers. ...
arXiv:1909.01495v1
fatcat:m5nkz3tdpncslgibl4bcgvlica
Exploring the Role of Prior Beliefs for Argument Persuasion
2018
Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
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religious ideology. ...
To study the actual effect of language use vs. prior beliefs on persuasion, we provide a new dataset and propose a controlled setting that takes into consideration two reader level factors: political and ...
We also treat this as a classification task 5 using the BIGISSUES vectors for each user as features and the user's religious and political ideology as the labels to be predicted. ...
doi:10.18653/v1/n18-1094
dblp:conf/naacl/DurmusC18
fatcat:nq6zii6yqnbpniiziipaazblia
Fine-grained Prediction of Political Leaning on Social Media with Unsupervised Deep Learning
2022
The Journal of Artificial Intelligence Research
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Predicting the political leaning of social media users is an increasingly popular task, given its usefulness for electoral forecasts, opinion dynamics models and for studying the political dimension of ...
Our technique leverages a deep neural network for learning latent political ideologies in a representation learning task. ...
For each selected user, we use the party classifier C to predict the political relevance of all the tweets in the user's timeline. ...
doi:10.1613/jair.1.13112
fatcat:x3jhn7kerbebbnuev24kmxsd7m
Tweets2Stance: Users stance detection exploiting Zero-Shot Learning Algorithms on Tweets
[article]
2022
arXiv
pre-print
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The ground-truth user's stance may come from Voting Advice Applications, online tools that help citizens to identify their political leanings by comparing their political preferences with party political ...
The work herein described focuses on a completely unsupervised stance detection framework that predicts the user's stance about specific social-political statements by exploiting content-based analysis ...
Acknowledgments We are immensely grateful to the Observatory on Political Parties and Representation [12] for providing us the 2019 official position of the six major Italian parties about 20 political ...
arXiv:2204.10710v1
fatcat:7fml5khur5hcfaty2ahpwc3tjq
Towards Understanding Persuasion in Computational Argumentation
[article]
2021
arXiv
pre-print
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We find that the users' prior beliefs and social interactions play an essential role in predicting their success in persuasion. ...
Finally, we explore the importance of incorporating contextual information to predict argument impact and show improvements compared to encoding only the text of the arguments. ...
ideology, income level, education level, and the political party they support. ...
arXiv:2110.01078v1
fatcat:dss7or3cmbas3fdrcx25xzyxma
Political Dimensionality Estimation Using a Probabilistic Graphical Model
2016
Conference on Uncertainty in Artificial Intelligence
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This paper attempts to move beyond the left-right characterization of political ideologies. We propose a trait based probabilistic model for estimating the manifold of political opinion. ...
are enough to represent peoples' entire political opinion. ...
When the ideology of parties spans multiple issues, representing these ideologies requires a political spectrum -a system for classifying different political positions using several geometric axes, each ...
dblp:conf/uai/LewenbergBBK16
fatcat:jijdhsv2qvbkndr7nrzart6bzq
An Integrated Model for User Attribute Discovery: A Case Study on Political Affiliation Identification
[chapter]
2014
Lecture Notes in Computer Science
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Our model achieved an accuracy of 70.1% for user party detection task. ...
We evaluated our method on a case study of user political affiliation identification, and compared against state-of-the-art baselines. ...
[9] proposed a system that uses linguistic analysis to generate attitude vectors on ideological datasets. ...
doi:10.1007/978-3-319-06608-0_36
fatcat:o6xkausj3fg5ngwq2mkimbjpna
Stance Detection on Social Media: State of the Art and Trends
[article]
2020
arXiv
pre-print
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Stance detection on social media is an emerging opinion mining paradigm for various social and political applications wheresentiment analysis might be seen sub-optimal. ...
An exhaustive review of stance detection techniques on social media ispresented, including the task definition, the different types of targets in stance detection, the features set used, and the variousmachine ...
a user's ideological stance for an event. ...
arXiv:2006.03644v1
fatcat:hw3qqg2k3vbkjodef764c46ajy
Predicting Online Islamophobic Behavior after #ParisAttacks
2018
Journal of Web Science
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on Twitter to build a classifier to predict post-event stance. ...
Specifically, we focus on how a person's online content and network dynamics can be used to predict future attitudes and stance in the aftermath of a major event. ...
Subsequent qualitative analysis of these features can shed light on personal, social and political attributes that are predictive of a user's stance. ...
doi:10.1561/106.00000013
dblp:journals/jws/DarwishMRBA18
fatcat:j6dtiw4snvfq3dpp33drfjrioe
A Machine Learning Pipeline to Examine Political Bias with Congressional Speeches
[article]
2021
arXiv
pre-print
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to predict political bias. ...
Political bias in social media has been studied in multiple viewpoints like media bias, political ideology, echo chambers, and controversies using machine learning pipelines. ...
political parties. ...
arXiv:2109.09014v1
fatcat:e6vwafinfrel7ellyygla7qfr4
The politics and analytics of health policy
2014
International Journal of Health Policy and Management
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politics to choice amongst different tribes of technocrats using different discourse for their core party support from that which they use to the centre-ground, and which constrains their policy when ...
' Cold War of the 1950s, but in the sense that 'we are all capitalists now' , a stance often disguised as the seemingly more neutral statement that the scope of politics is diminished by allegedly inexorable ...
doi:10.15171/ijhpm.2014.26
pmid:24757685
pmcid:PMC3992783
fatcat:tfbdg2v7xjghzh6bjuristmw3i
Joint Non-negative Matrix Factorization for Learning Ideological Leaning on Twitter
[article]
2017
arXiv
pre-print
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In this paper, we use a machine-learning approach to learn a liberal-conservative ideology space on Twitter, and show how we can use the learned latent space to tackle the filter bubble problem. ...
Finally, we demonstrate the utility of our model in real-world scenarios, by illustrating how the learned ideology latent space can be used to develop exploratory and interactive interfaces that can help ...
We de ne ideology based on the policy dimension that articulates a user's political preference. Our de nition is inspired by work in political-science literature, such as work by Bafumi et al. ...
arXiv:1711.10251v1
fatcat:uvmme6ehfjcfzb2t3qb2gubicm
Political Homophily in Independence Movements: Analysing and Classifying Social Media Users by National Identity
[article]
2018
arXiv
pre-print
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Social media and data mining are increasingly being used to analyse political and societal issues. ...
Citizens with common national identities can also vote for parties with different political ideologies, and their national identities can be instead motivated by cultural and linguistic backgrounds [7 ...
supporters of other parties. ...
arXiv:1702.08388v3
fatcat:hhgu2owgjzdn5oxksewl5ihkeq
Facilitating Diverse Political Engagement with the Living Voters Guide
2012
Journal of Information Technology & Politics
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In this article, we use a point view as an indicator of a user's desire to access both pros and cons. Like point expansions, point views are not a precise measure of a user's reading activity. ...
to a politics of mobilization and ideological community-building (Farrell & Drezner, 2008; Karpf, 2008; Kerbel, 2009 ). ...
doi:10.1080/19331681.2012.665755
fatcat:qtvrw4uhifffzkebtl3qeswm54
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