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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:

More than Bags of Words: Sentiment Analysis with Word Embeddings
Elena Rudkowsky, Martin Haselmayer, Matthias Wastian, et al.
Communication Methods and Measures (2018) Vol. 12, Iss. 2-3, pp. 140-157
Open Access | Times Cited: 186

Showing 1-25 of 186 citing articles:

The Validity of Sentiment Analysis: Comparing Manual Annotation, Crowd-Coding, Dictionary Approaches, and Machine Learning Algorithms
Wouter van Atteveldt, Mariken Anna Catharina Geertruida van der Velden, Mark Boukes
Communication Methods and Measures (2021) Vol. 15, Iss. 2, pp. 121-140
Open Access | Times Cited: 266
When Communication Meets Computation: Opportunities, Challenges, and Pitfalls in Computational Communication Science
Wouter van Atteveldt, Tai‐Quan Peng
Communication Methods and Measures (2018) Vol. 12, Iss. 2-3, pp. 81-92
Open Access | Times Cited: 174
From Text to Thought: How Analyzing Language Can Advance Psychological Science
Joshua Conrad Jackson, Joseph Watts, Johann‐Mattis List, et al.
Perspectives on Psychological Science (2021) Vol. 17, Iss. 3, pp. 805-826
Open Access | Times Cited: 112
Evaluation of Speech-Based Digital Biomarkers: Review and Recommendations
Jessica Robin, John Harrison, Liam D. Kaufman, et al.
Digital Biomarkers (2020) Vol. 4, Iss. 3, pp. 99-108
Open Access | Times Cited: 112
What’s the Tone? Easy Doesn’t Do It: Analyzing Performance and Agreement Between Off-the-Shelf Sentiment Analysis Tools
Mark Boukes, Bob van de Velde, Theo Araujo, et al.
Communication Methods and Measures (2019) Vol. 14, Iss. 2, pp. 83-104
Open Access | Times Cited: 104
Negative campaigning and its consequences: a review and a look ahead
Martin Haselmayer
French Politics (2019) Vol. 17, Iss. 3, pp. 355-372
Open Access | Times Cited: 100
What’s in a post? How sentiment and issue salience affect users’ emotional reactions on Facebook
Jakob‐Moritz Eberl, Petro Tolochko, Pablo Jost, et al.
Journal of Information Technology & Politics (2020) Vol. 17, Iss. 1, pp. 48-65
Open Access | Times Cited: 95
A Timely Intervention: Tracking the Changing Meanings of Political Concepts with Word Vectors
Emma Rodman
Political Analysis (2019) Vol. 28, Iss. 1, pp. 87-111
Closed Access | Times Cited: 88
Latent Semantic Scaling: A Semisupervised Text Analysis Technique for New Domains and Languages
Kohei Watanabe
Communication Methods and Measures (2020) Vol. 15, Iss. 2, pp. 81-102
Open Access | Times Cited: 85
Aspect Based Twitter Sentiment Analysis on Vaccination and Vaccine Types in COVID-19 Pandemic With Deep Learning
İrfan Aygün, Buket Kaya, Mehmet Kaya
IEEE Journal of Biomedical and Health Informatics (2021) Vol. 26, Iss. 5, pp. 2360-2369
Closed Access | Times Cited: 73
What drives the helpfulness of online reviews? A deep learning study of sentiment analysis, pictorial content and reviewer expertise for mature destinations
José Enrique Bigné Alcañiz, Carla Ruíz Mafé, Antonio Carlos Cuenca Ballester, et al.
Journal of Destination Marketing & Management (2021) Vol. 20, pp. 100570-100570
Open Access | Times Cited: 63
Creating and Comparing Dictionary, Word Embedding, and Transformer-Based Models to Measure Discrete Emotions in German Political Text
Tobias Widmann, Maximilian Wich
Political Analysis (2022) Vol. 31, Iss. 4, pp. 626-641
Open Access | Times Cited: 44
Ability of ChatGPT to generate competent radiology reports for distal radius fracture by use of RSNA template items and integrated AO classifier
Wolfram A. Bosbach, Jan F. Senge, Bence Németh, et al.
Current Problems in Diagnostic Radiology (2023) Vol. 53, Iss. 1, pp. 102-110
Open Access | Times Cited: 37
Deep neural networks and weighted word embeddings for sentiment analysis of drug product reviews
Derwin Suhartono, Kartika Purwandari, Nicholaus Hendrik Jeremy, et al.
Procedia Computer Science (2023) Vol. 216, pp. 664-671
Open Access | Times Cited: 35
Using Machine Learning to Identify Health Outcomes from Electronic Health Record Data
Jenna Wong, Mara E. Murray Horwitz, Li Zhou, et al.
Current Epidemiology Reports (2018) Vol. 5, Iss. 4, pp. 331-342
Open Access | Times Cited: 83
Classification of Poetry Text Into the Emotional States Using Deep Learning Technique
Shakeel Ahmad, Muhammad Zubair Asghar, Fahad Alotaibi, et al.
IEEE Access (2020) Vol. 8, pp. 73865-73878
Open Access | Times Cited: 59
Does Radical-Right Success Make the Political Debate More Negative? Evidence from Emotional Rhetoric in German State Parliaments
Vicente Valentim, Tobias Widmann
Political Behavior (2021) Vol. 45, Iss. 1, pp. 243-264
Open Access | Times Cited: 55
Text-mining forma mentis networks reconstruct public perception of the STEM gender gap in social media
Massimo Stella
PeerJ Computer Science (2020) Vol. 6, pp. e295-e295
Open Access | Times Cited: 52
A Hybrid Deep Learning Technique for Personality Trait Classification From Text
Hussain Al-Ahmad, Muhammad Zubair Asghar, Muhammad Zubair Asghar, et al.
IEEE Access (2021) Vol. 9, pp. 146214-146232
Open Access | Times Cited: 50
A Content and Sentiment Analysis of Greek Tweets during the Pandemic
Dimitrios Kydros, Maria Argyropoulou, Vasiliki Vrana
Sustainability (2021) Vol. 13, Iss. 11, pp. 6150-6150
Open Access | Times Cited: 41
Arabic Sentiment Analysis Based on Word Embeddings and Deep Learning
Nasrin Elhassan, Giuseppe Varone, Rami Ahmed, et al.
Computers (2023) Vol. 12, Iss. 6, pp. 126-126
Open Access | Times Cited: 22
Cross-Lingual Classification of Political Texts Using Multilingual Sentence Embeddings
Hauke Licht
Political Analysis (2023) Vol. 31, Iss. 3, pp. 366-379
Closed Access | Times Cited: 19
Are customer star ratings and sentiments aligned? A deep learning study of the customer service experience in tourism destinations
José Enrique Bigné Alcañiz, Carla Ruíz Mafé, Carmen Pérez Cabañero, et al.
Service Business (2023) Vol. 17, Iss. 1, pp. 281-314
Open Access | Times Cited: 18
Sentiment Analysis of COVID-19 Tweets Using Adaptive Neuro-Fuzzy Inference System Models
Sabri Mohammed, Brahami Menaouer, Abid Faten Fatima Zohra, et al.
International Journal of Software Science and Computational Intelligence (2022) Vol. 14, Iss. 1, pp. 1-20
Closed Access | Times Cited: 27
CitEnergy : A BERT based model to analyse Citizens’ Energy-Tweets
Jatin Bedi, Durga Toshniwal
Sustainable Cities and Society (2022) Vol. 80, pp. 103706-103706
Closed Access | Times Cited: 26
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