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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

The emergence of social media data and sentiment analysis in election prediction
Priyavrat Chauhan, Nonita Sharma, Geeta Sikka
Journal of Ambient Intelligence and Humanized Computing (2020) Vol. 12, Iss. 2, pp. 2601-2627
Closed Access | Times Cited: 154

Showing 1-25 of 154 citing articles:

Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study
Zenun Kastrati, Fisnik Dalipi, Ali Shariq Imran, et al.
Applied Sciences (2021) Vol. 11, Iss. 9, pp. 3986-3986
Open Access | Times Cited: 161
Transformer-based deep learning models for the sentiment analysis of social media data
Sayyida Tabinda Kokab, Sohail Asghar, Shehneela Naz
Array (2022) Vol. 14, pp. 100157-100157
Open Access | Times Cited: 99
Effect of public sentiment on stock market movement prediction during the COVID-19 outbreak
Nabanita Das, Bikash Sadhukhan, Tanusree Chatterjee, et al.
Social Network Analysis and Mining (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 37
A Deep Learning Sentiment Analyser for Social Media Comments in Low-Resource Languages
Zenun Kastrati, Lule Ahmedi, Arianit Kurti, et al.
Electronics (2021) Vol. 10, Iss. 10, pp. 1133-1133
Open Access | Times Cited: 44
Joint multimodal sentiment analysis based on information relevance
Danlei Chen, Wang Su, Peng Wu, et al.
Information Processing & Management (2022) Vol. 60, Iss. 2, pp. 103193-103193
Closed Access | Times Cited: 27
Sentiment, we-talk and engagement on social media: insights from Twitter data mining on the US presidential elections 2020
Linus Hagemann, Olga Abramova
Internet Research (2023) Vol. 33, Iss. 6, pp. 2058-2085
Closed Access | Times Cited: 18
Investigating Deep Stock Market Forecasting with Sentiment Analysis
Charalampos M. Liapis, Aikaterini Karanikola, Sotiris Kotsiantis
Entropy (2023) Vol. 25, Iss. 2, pp. 219-219
Open Access | Times Cited: 17
Public Opinion Mining on Construction Health and Safety: Latent Dirichlet Allocation Approach
Liyun Zeng, Rita Yi Man Li, Tan Yiğitcanlar, et al.
Buildings (2023) Vol. 13, Iss. 4, pp. 927-927
Open Access | Times Cited: 16
Comprehensive review and comparative analysis of transformer models in sentiment analysis
Hadis Bashiri, Hassan Naderi
Knowledge and Information Systems (2024)
Closed Access | Times Cited: 5
A systematic literature review of how and whether social media data can complement traditional survey data to study public opinion
Maud Reveilhac, Stephanie Steinmetz, Davide Morselli
Multimedia Tools and Applications (2022) Vol. 81, Iss. 7, pp. 10107-10142
Open Access | Times Cited: 25
A cooperative deep learning model for fake news detection in online social networks
Chandrakant Mallick, Sarojananda Mishra, Manas Ranjan Senapati
Journal of Ambient Intelligence and Humanized Computing (2023) Vol. 14, Iss. 4, pp. 4451-4460
Open Access | Times Cited: 13
A comprehensive analysis of forecasting elections using social media text
Abhishek Gaur, Dharmendra Kumar Yadav
Multimedia Tools and Applications (2025)
Closed Access
Dynamic Text Augmentation for Robust Sentiment Analysis: Enhancing Model Performance with EDA and Multi-Channel CNN
Komang Wahyu Trisna, Jinjie Huang, Yuanjian Chen, et al.
IEEE Access (2025) Vol. 13, pp. 31978-31991
Open Access
Comparison of Machine Learning Models for Sentiment Analysis of Big Turkish Web-Based Data
Cemile Gökçe Özmen, Selim Gündüz
Applied Sciences (2025) Vol. 15, Iss. 5, pp. 2297-2297
Open Access
TaNTISA: a hybrid approach for text/non-text classification and sentiment analysis of multimodal social media images
Priyavrat Chauhan, Nonita Sharma, Geeta Sikka
Sadhana (2025) Vol. 50, Iss. 1
Closed Access
Graph-aware pre-trained language model for political sentiment analysis in Filipino social media
Jean Aristide Aquino, Di Jie Liew, Yung‐Chun Chang
Engineering Applications of Artificial Intelligence (2025) Vol. 146, pp. 110317-110317
Closed Access
Model Framework for Discovering and Utilizing Public Opinion Hot Topic Knowledge in the Social Media Network Environment
Yun Liu
International Journal of Intelligent Information Technologies (2025) Vol. 21, Iss. 1, pp. 1-25
Open Access
The Dawn of the Human-Machine Era: A forecast of new and emerging language technologies
Dave Sayers, Rui Sousa‐Silva, Sviatlana Höhn, et al.
(2021)
Open Access | Times Cited: 30
Machine learning for predicting elections in Latin America based on social media engagement and polls
Kellyton Brito, Paulo J. L. Adeodato
Government Information Quarterly (2022) Vol. 40, Iss. 1, pp. 101782-101782
Open Access | Times Cited: 21
Assessing BERT’s ability to learn Italian syntax: a study on null-subject and agreement phenomena
Raffaele Guarasci, Stefano Silvestri, Giuseppe De Pietro, et al.
Journal of Ambient Intelligence and Humanized Computing (2021) Vol. 14, Iss. 1, pp. 289-303
Closed Access | Times Cited: 24
Using Social Media & Sentiment Analysis to Make Investment Decisions
Ben Hasselgren, Christos Chrysoulas, Nikolaos Pitropakis, et al.
Future Internet (2022) Vol. 15, Iss. 1, pp. 5-5
Open Access | Times Cited: 18
Measuring the performances of politicians on social media and the correlation with major Latin American election results
Kellyton Brito, Paulo J. L. Adeodato
Government Information Quarterly (2022) Vol. 39, Iss. 4, pp. 101745-101745
Closed Access | Times Cited: 16
Analysis and prediction of Indian stock market: a machine-learning approach
Shilpa Srivastava, Millie Pant, V. B. Gupta
International Journal of Systems Assurance Engineering and Management (2023) Vol. 14, Iss. 4, pp. 1567-1585
Closed Access | Times Cited: 8
An enhanced Wasserstein generative adversarial network with Gramian Angular Fields for efficient stock market prediction during market crash periods
Alireza Ghasemieh, Rasha Kashef
Applied Intelligence (2023) Vol. 53, Iss. 23, pp. 28479-28500
Closed Access | Times Cited: 8
How Does the World View China’s Carbon Policy? A Sentiment Analysis on Twitter Data
N. Xiang, Wang Li-mao, Shuai Zhong, et al.
Energies (2021) Vol. 14, Iss. 22, pp. 7782-7782
Open Access | Times Cited: 19
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