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Authors: Athanasios Lyras 1 ; Sotiria Vernikou 1 ; Andreas Kanavos 2 ; Spyros Sioutas 1 and Phivos Mylonas 3

Affiliations: 1 Computer Engineering and Informatics Department, University of Patras, Patras, Greece ; 2 Department of Digital Media and Communication, Ionian University, Kefalonia, Greece ; 3 Department of Informatics, Ionian University, Corfu, Greece

Keyword(s): Big Data, Deep Learning, Deep Learning Neural Networks, LSTM, Natural Language Processing, Social Media, Text Mining, Trust Modeling, Twitter.

Abstract: Communication accounts for a vital need among people in order to express and exchange ideas, emotions, messages, etc. Social media fulfill this necessity as users can make use of a variety of platforms like Twitter, to leave their digital fingerprint by uploading personal data. The ever humongous volume of users claims for evaluation and that is why the subject of user credibility or trust in a social network is equally vital and meticulously discussed in this paper. Specifically, a trust method, as we measure user credibility and trust in a social environment using user metrics, is proposed. Our dataset is derived from Twitter and consists of tweets from a popular television series. Initially, our text data are analyzed and preprocessed using NLP tools and in following, a balanced dataset that serves in model evaluation and parameter tuning, is constructed. A deep learning forecasting model, which uses LSTM/BiLSTM layers along with classic Artificial Neural Network (ANN) and predict s user credibility, is accessed for its worth in terms of model accuracy. (More)

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Paper citation in several formats:
Lyras, A.; Vernikou, S.; Kanavos, A.; Sioutas, S. and Mylonas, P. (2021). Modeling Credibility in Social Big Data using LSTM Neural Networks. In Proceedings of the 17th International Conference on Web Information Systems and Technologies - DMMLACS, ISBN 978-989-758-536-4; ISSN 2184-3252, pages 599-606. DOI: 10.5220/0010726600003058

@conference{dmmlacs21,
author={Athanasios Lyras. and Sotiria Vernikou. and Andreas Kanavos. and Spyros Sioutas. and Phivos Mylonas.},
title={Modeling Credibility in Social Big Data using LSTM Neural Networks},
booktitle={Proceedings of the 17th International Conference on Web Information Systems and Technologies - DMMLACS,},
year={2021},
pages={599-606},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010726600003058},
isbn={978-989-758-536-4},
issn={2184-3252},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Web Information Systems and Technologies - DMMLACS,
TI - Modeling Credibility in Social Big Data using LSTM Neural Networks
SN - 978-989-758-536-4
IS - 2184-3252
AU - Lyras, A.
AU - Vernikou, S.
AU - Kanavos, A.
AU - Sioutas, S.
AU - Mylonas, P.
PY - 2021
SP - 599
EP - 606
DO - 10.5220/0010726600003058