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Investigating Patterns of Influence ...
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Hanley, Hans William Alexander,
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Investigating Patterns of Influence and Propaganda Across International News Outlets /
Record Type:
Electronic resources : Monograph/item
Title/Author:
Investigating Patterns of Influence and Propaganda Across International News Outlets // Hans William Alexander Hanley.
Author:
Hanley, Hans William Alexander,
Description:
1 electronic resource (232 pages)
Notes:
Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
Contained By:
Dissertations Abstracts International86-12B.
Subject:
Websites. -
Online resource:
https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31974630
ISBN:
9798311950893
Investigating Patterns of Influence and Propaganda Across International News Outlets /
Hanley, Hans William Alexander,
Investigating Patterns of Influence and Propaganda Across International News Outlets /
Hans William Alexander Hanley. - 1 electronic resource (232 pages)
Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
Misinformation, propaganda, and disinformation undermine trust in institutions, spread falsehoods, and, at times, incite violence. However, recent advancements in transformer-based AI models offer new opportunities to combat the global proliferation of these specious narratives in near real time. In this thesis, we propose and develop a system that leverages these models to scalably identify, track, and analyze the spread of narratives across thousands of news websites.In the following thesis, we first demonstrate how pre-trained off-the-shelf models can be used to track the dissemination of news narratives from known propaganda websites to social media platforms such as Reddit and Telegram. Second, we illustrate how these methods can be enhanced by fine-tuning these pre-trained models to handle multiple languages and different levels of semantic similarity granularity. We similarly propose novel means of stance detection to enable a deeper understanding of the perspectives and positions expressed in news articles and social media posts. Finally, we propose a system to continuously scrape and gather news articles from thousands of websites, allowing the tracking of the spread of news narratives, misinformation, propaganda, and disinformation in near real time. By employing our novel embeddings and different types of clustering techniques, this proposed system identifies news stories, topics, and themes across these thousands of news websites. Then by utilizing stance detection, this system assesses the biases in news articles, enabling the identification of websites that spread slanted propaganda or misinformation. Ultimately, through network inference methods and natural language inference, this system finally uncovers connections among websites disseminating slanted or false content.
English
ISBN: 9798311950893Subjects--Topical Terms:
1062467
Websites.
Investigating Patterns of Influence and Propaganda Across International News Outlets /
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Misinformation, propaganda, and disinformation undermine trust in institutions, spread falsehoods, and, at times, incite violence. However, recent advancements in transformer-based AI models offer new opportunities to combat the global proliferation of these specious narratives in near real time. In this thesis, we propose and develop a system that leverages these models to scalably identify, track, and analyze the spread of narratives across thousands of news websites.In the following thesis, we first demonstrate how pre-trained off-the-shelf models can be used to track the dissemination of news narratives from known propaganda websites to social media platforms such as Reddit and Telegram. Second, we illustrate how these methods can be enhanced by fine-tuning these pre-trained models to handle multiple languages and different levels of semantic similarity granularity. We similarly propose novel means of stance detection to enable a deeper understanding of the perspectives and positions expressed in news articles and social media posts. Finally, we propose a system to continuously scrape and gather news articles from thousands of websites, allowing the tracking of the spread of news narratives, misinformation, propaganda, and disinformation in near real time. By employing our novel embeddings and different types of clustering techniques, this proposed system identifies news stories, topics, and themes across these thousands of news websites. Then by utilizing stance detection, this system assesses the biases in news articles, enabling the identification of websites that spread slanted propaganda or misinformation. Ultimately, through network inference methods and natural language inference, this system finally uncovers connections among websites disseminating slanted or false content.
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https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31974630
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