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Combined Word and Network Embeddings...

Singh, Tannu Dharmendra.

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Combined Word and Network Embeddings: An Analysis Framework of User Opinions on Social Media.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Combined Word and Network Embeddings: An Analysis Framework of User Opinions on Social Media./
作者:	Singh, Tannu Dharmendra.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2020,
面頁冊數:	56 p.
附註:	Source: Masters Abstracts International, Volume: 82-02.
Contained By:	Masters Abstracts International82-02.
標題:	Computer science. -
電子資源:	https://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28086851
ISBN:	9798664718515

Combined Word and Network Embeddings: An Analysis Framework of User Opinions on Social Media.
Singh, Tannu Dharmendra.

Combined Word and Network Embeddings: An Analysis Framework of User Opinions on Social Media. - Ann Arbor : ProQuest Dissertations & Theses, 2020 - 56 p.

Source: Masters Abstracts International, Volume: 82-02.

Thesis (M.S.)--The University of North Carolina at Charlotte, 2020.

This item must not be sold to any third party vendors.

Online social media like Twitter, Facebook, and Gab is often used as the stage to deliver one's opinion for a particular group of people, a political party, etc. Sometimes, the opinions shared are considered as controversial by some audience, applauded by some, or disagreed by some in the form of comments, sharing, likes, or dislikes. The information about shared opinion and the reaction to it in the form of positive, or negative reaction forms an interaction, and a collection of many such interactions forms a signed network. In addition, the evolution of information on social networks strongly relies on the nature of interactions between the users. The study of interactions is, therefore, crucial to predict the extent and nature of information spread. In this work, we study the relationship between users whether they agree or disagree in the dynamic evolution of interactions (cascades) on a larger network, Gab, to predict the relationship between the users on the social network. We quantitatively use the combination of text information and network information to enhance state of the art deep learning models for contradiction detection. The outcome of this research might contribute to improving link prediction.

ISBN: 9798664718515Subjects--Topical Terms:

523869
Computer science.
Subjects--Index Terms:

Combined

Combined Word and Network Embeddings: An Analysis Framework of User Opinions on Social Media.
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500 $a Source: Masters Abstracts International, Volume: 82-02.
500 $a Advisor: Krishnan, Siddharth.
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506 $a This item must not be sold to any third party vendors.
520 $a Online social media like Twitter, Facebook, and Gab is often used as the stage to deliver one's opinion for a particular group of people, a political party, etc. Sometimes, the opinions shared are considered as controversial by some audience, applauded by some, or disagreed by some in the form of comments, sharing, likes, or dislikes. The information about shared opinion and the reaction to it in the form of positive, or negative reaction forms an interaction, and a collection of many such interactions forms a signed network. In addition, the evolution of information on social networks strongly relies on the nature of interactions between the users. The study of interactions is, therefore, crucial to predict the extent and nature of information spread. In this work, we study the relationship between users whether they agree or disagree in the dynamic evolution of interactions (cascades) on a larger network, Gab, to predict the relationship between the users on the social network. We quantitatively use the combination of text information and network information to enhance state of the art deep learning models for contradiction detection. The outcome of this research might contribute to improving link prediction.
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650 4 $a Social networks. $3 556983
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653 $a Networks
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690 $a 0626
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