short-paper

A Graph-Theoretic Embedding-Based Approach for Rumor Detection in Twitter

Authors:

Muhammad Abulaish,

Basanta SinghAuthors Info & Claims

WI '19: IEEE/WIC/ACM International Conference on Web Intelligence

Pages 466 - 470

https://doi.org/10.1145/3350546.3352569

Published: 14 October 2019 Publication History

Abstract

In this paper, we present a graph-theoretic embedding-based approach to model user-generated contents in online social media for rumor detection. Starting with a small set of seed rumor words of four different lexical categories, we generate a words co-occurrence graph and apply centrality-based analysis to identify prominent rumor characterizing words. Thereafter, word embedding is applied to represent each category of seed words as numeric vectors and to train three different classification models for rumor detection. The performance of the proposed approach is empirically evaluated over two versions of a benchmark dataset. The proposed approach is also compared with one of the state-of-the-art methods for rumor detection and performs significantly better.

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Cited By

Chen XJian YKe LQiu YChen XSong YWang H(2024)A deep semantic-aware approach for Cantonese rumor detection in social networks with graph convolutional networkExpert Systems with Applications10.1016/j.eswa.2023.123007245(123007)Online publication date: Jul-2024
https://doi.org/10.1016/j.eswa.2023.123007
Khan SFazil MImoize AAlabduallah BAlbahlal BAlajlan SAlmjally ASiddiqui T(2023)Transformer Architecture-Based Transfer Learning for Politeness Prediction in ConversationSustainability10.3390/su15141082815:14(10828)Online publication date: 10-Jul-2023
https://doi.org/10.3390/su151410828
Yuan SYang Q(2023)Network Rumor Detection Using Attention Mechanism and BiGRU Neural Network in Big Data EnvironmentJournal of Circuits, Systems and Computers10.1142/S021812662450009933:01Online publication date: 14-Sep-2023
https://doi.org/10.1142/S0218126624500099
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A Graph-Theoretic Embedding-Based Approach for Rumor Detection in Twitter

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cover image ACM Other conferences

WI '19: IEEE/WIC/ACM International Conference on Web Intelligence

October 2019

507 pages

ISBN:9781450369343

DOI:10.1145/3350546

Copyright © 2019 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 14 October 2019

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WI '19

WI '19: IEEE/WIC/ACM International Conference on Web Intelligence

October 14 - 17, 2019

Thessaloniki, Greece

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Overall Acceptance Rate 118 of 178 submissions, 66%

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Cited By

Chen XJian YKe LQiu YChen XSong YWang H(2024)A deep semantic-aware approach for Cantonese rumor detection in social networks with graph convolutional networkExpert Systems with Applications10.1016/j.eswa.2023.123007245(123007)Online publication date: Jul-2024
https://doi.org/10.1016/j.eswa.2023.123007
Khan SFazil MImoize AAlabduallah BAlbahlal BAlajlan SAlmjally ASiddiqui T(2023)Transformer Architecture-Based Transfer Learning for Politeness Prediction in ConversationSustainability10.3390/su15141082815:14(10828)Online publication date: 10-Jul-2023
https://doi.org/10.3390/su151410828
Yuan SYang Q(2023)Network Rumor Detection Using Attention Mechanism and BiGRU Neural Network in Big Data EnvironmentJournal of Circuits, Systems and Computers10.1142/S021812662450009933:01Online publication date: 14-Sep-2023
https://doi.org/10.1142/S0218126624500099
Fazil MKhan SAlbahlal BAlotaibi RSiddiqui TShah M(2023)Attentional Multi-Channel Convolution With Bidirectional LSTM Cell Toward Hate Speech PredictionIEEE Access10.1109/ACCESS.2023.324638811(16801-16811)Online publication date: 2023
https://doi.org/10.1109/ACCESS.2023.3246388
Serpanos DXenos GTsouvalas B(2022)Location and Language Independent Fake Rumor Detection Through Epidemiological and Structural Graph Analysis of Social ConnectionsFrontiers in Artificial Intelligence10.3389/frai.2022.7343475Online publication date: 27-Apr-2022
https://doi.org/10.3389/frai.2022.734347
Khan SKamal AFazil MAlshara MSejwal VAlotaibi RBaig AAlqahtani S(2022)HCovBi-Caps: Hate Speech Detection Using Convolutional and Bi-Directional Gated Recurrent Unit With Capsule NetworkIEEE Access10.1109/ACCESS.2022.314379910(7881-7894)Online publication date: 2022
https://doi.org/10.1109/ACCESS.2022.3143799
Fazil MSah AAbulaish M(2021)DeepSBD: A Deep Neural Network Model With Attention Mechanism for SocialBot DetectionIEEE Transactions on Information Forensics and Security10.1109/TIFS.2021.310249816(4211-4223)Online publication date: 1-Jan-2021
https://dl.acm.org/doi/10.1109/TIFS.2021.3102498
Nagaraj PDas B(2021)Graph Convolution-Based Joint Learning of Rumor with Content, User Credibility, Propagation Context, and Cognitive as Well as Emotion SignalsSentimental Analysis and Deep Learning10.1007/978-981-16-5157-1_9(113-128)Online publication date: 26-Oct-2021
https://doi.org/10.1007/978-981-16-5157-1_9
Yang HXu ZLiu LTian JZhang Y(2020)Adaptive Slide Window-Based Feature Cognition for Deceptive Information IdentificationIEEE Access10.1109/ACCESS.2020.30110728(134311-134323)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.3011072

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