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OpenAlex Citation Counts

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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:

Lexicon-enhanced sentiment analysis framework using rule-based classification scheme
Muhammad Zubair Asghar, Irfan Ullah Khan, Shakeel Ahmad, et al.
PLoS ONE (2017) Vol. 12, Iss. 2, pp. e0171649-e0171649
Open Access | Times Cited: 156

Showing 1-25 of 156 citing articles:

A survey of sentiment analysis in social media
Lin Yue, Weitong Chen, Xue Li, et al.
Knowledge and Information Systems (2018) Vol. 60, Iss. 2, pp. 617-663
Closed Access | Times Cited: 455
Sentiment Analysis for E-Commerce Product Reviews in Chinese Based on Sentiment Lexicon and Deep Learning
Li Yang, Ying Li, Jin Wang, et al.
IEEE Access (2020) Vol. 8, pp. 23522-23530
Open Access | Times Cited: 442
A Study on Sentiment Analysis Techniques of Twitter Data
Abdullah Alsaeedi, Mohammad Zubair
International Journal of Advanced Computer Science and Applications (2019) Vol. 10, Iss. 2
Open Access | Times Cited: 245
Sentiment Analysis in Health and Well-Being: Systematic Review
Anastazia Žunić, Padraig Corcoran, ‪Irena Spasić
JMIR Medical Informatics (2019) Vol. 8, Iss. 1, pp. e16023-e16023
Open Access | Times Cited: 163
Detection and classification of social media-based extremist affiliations using sentiment analysis techniques
Shakeel Ahmad, Muhammad Zubair Asghar, Fahad Alotaibi, et al.
Human-centric Computing and Information Sciences (2019) Vol. 9, Iss. 1
Open Access | Times Cited: 155
Improving the Performance of Sentiment Analysis of Tweets Containing Fuzzy Sentiment Using the Feature Ensemble Model
Huyen Trang Phan, Cuong Tran, Ngoc Thanh Nguyên, et al.
IEEE Access (2020) Vol. 8, pp. 14630-14641
Open Access | Times Cited: 143
Stress detection using natural language processing and machine learning over social interactions
Tanya Nijhawan, Girija Attigeri, T Ananthakrishna
Journal Of Big Data (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 90
A novel method for sentiment classification of drug reviews using fusion of deep and machine learning techniques
Mohammad Ehsan Basiri, Moloud Abdar, Mehmet Akif Çifçi, et al.
Knowledge-Based Systems (2020) Vol. 198, pp. 105949-105949
Closed Access | Times Cited: 132
The impact of preprocessing steps on the accuracy of machine learning algorithms in sentiment analysis
Saqib Alam, Nianmin Yao
Computational and Mathematical Organization Theory (2018) Vol. 25, Iss. 3, pp. 319-335
Closed Access | Times Cited: 108
Multimodal sentimental analysis for social media applications: A comprehensive review
Ganesh Chandrasekaran, Tu N. Nguyen, D. Jude Hemanth
Wiley Interdisciplinary Reviews Data Mining and Knowledge Discovery (2021) Vol. 11, Iss. 5
Closed Access | Times Cited: 100
Fuzzy Ontology and LSTM-Based Text Mining: A Transportation Network Monitoring System for Assisting Travel
Farman Ali, Shaker El–Sappagh, Daehan Kwak
Sensors (2019) Vol. 19, Iss. 2, pp. 234-234
Open Access | Times Cited: 87
Imbalanced text sentiment classification using universal and domain-specific knowledge
Yijing Li, Haixiang Guo, Qingpeng Zhang, et al.
Knowledge-Based Systems (2018) Vol. 160, pp. 1-15
Closed Access | Times Cited: 85
Sentiment analysis of Chinese stock reviews based on BERT model
Mingzheng Li, Lei Chen, Jing Zhao, et al.
Applied Intelligence (2021) Vol. 51, Iss. 7, pp. 5016-5024
Closed Access | Times Cited: 69
Topics and Sentiments of Public Concerns Regarding COVID-19 Vaccines: Social Media Trend Analysis
Michal Monselise, Chia‐Hsuan Chang, Gustavo Ferreira, et al.
Journal of Medical Internet Research (2021) Vol. 23, Iss. 10, pp. e30765-e30765
Open Access | Times Cited: 62
Advances in Sentiment Analysis - Techniques, Applications, and Challenges
Jinfeng Li
Artificial intelligence (2023)
Open Access | Times Cited: 38
T‐SAF: Twitter sentiment analysis framework using a hybrid classification scheme
Muhammad Zubair Asghar, Fazal Masud Kundi, Shakeel Ahmad, et al.
Expert Systems (2017) Vol. 35, Iss. 1
Open Access | Times Cited: 82
Opinion mining on large scale data using sentiment analysis and k-means clustering
Sumbal Riaz, Mehvish Fatima, Muhammad Kamran, et al.
Cluster Computing (2017) Vol. 22, Iss. S3, pp. 7149-7164
Closed Access | Times Cited: 78
Enhanced Twitter Sentiment Analysis Using Hybrid Approach and by Accounting Local Contextual Semantic
Itisha Gupta, Nisheeth Joshi
Journal of Intelligent Systems (2019) Vol. 29, Iss. 1, pp. 1611-1625
Open Access | Times Cited: 68
Opinion spam detection framework using hybrid classification scheme
Muhammad Zubair Asghar, Asmat Ullah, Shakeel Ahmad, et al.
Soft Computing (2019) Vol. 24, Iss. 5, pp. 3475-3498
Closed Access | Times Cited: 65
Sentence-Level Emotion Detection Framework Using Rule-Based Classification
Muhammad Zubair Asghar, Irfan Ullah Khan, Afsana Bibi, et al.
Cognitive Computation (2017) Vol. 9, Iss. 6, pp. 868-894
Closed Access | Times Cited: 63
Emotion AI-Driven Sentiment Analysis: A Survey, Future Research Directions, and Open Issues
Priya Chakriswaran, P. M. Durai Raj Vincent, Kathiravan Srinivasan, et al.
Applied Sciences (2019) Vol. 9, Iss. 24, pp. 5462-5462
Open Access | Times Cited: 61
Sentiment Analysis of Lithuanian Texts Using Traditional and Deep Learning Approaches
Jurgita Kapočiūtė-Dzikienė, Robertas Damaševičius, Marcin Woźniak
Computers (2019) Vol. 8, Iss. 1, pp. 4-4
Open Access | Times Cited: 59
“The Enemy Among Us”
Wafa Alorainy, Pete Burnap, Han Liu, et al.
ACM Transactions on the Web (2019) Vol. 13, Iss. 3, pp. 1-26
Open Access | Times Cited: 56
A Review of Different Approaches for Detecting Emotion from Text
Ashritha R Murthy, K. M. Anil Kumar
IOP Conference Series Materials Science and Engineering (2021) Vol. 1110, Iss. 1, pp. 012009-012009
Open Access | Times Cited: 55
Determining the Efficiency of Drugs Under Special Conditions From Users’ Reviews on Healthcare Web Forums
Eysha Saad, Sadia Din, Ramish Jamil, et al.
IEEE Access (2021) Vol. 9, pp. 85721-85737
Open Access | Times Cited: 47
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