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Exploring NLP‐Based Solutions to Social Media Moderation Challenges
Human Behavior and Emerging Technologies, Volume 2025, Issue 1, 2025.The rise of social media has revolutionized global communication, enabling users and businesses to connect, advertise, and monitor competitors. However, this expansion has also fueled toxic behaviors like hate speech and harassment, exposing innocent users to harmful content while overwhelming human moderators and impacting their well‐being. To address
Heba Saleous +3 more
wiley +1 more source
SemEval-2015 Task 9: CLIPEval Implicit Polarity of Events [PDF]
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), 2015 Sentiment analysis tends to focus on the po- larity of words, combining their values to de- tect which portion of a text is opinionated. CLIPEval wants to promote a more holistic approach, looking at psychological researches that frame the connotations of words as the emotional values activated by them.
Russo Irene +2 more
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IEEE AccessThis research addresses the challenge of multi-label emotion classification on imbalanced datasets using a BERT-based model. Emotion classification, essential for applications like social media analysis and sentiment monitoring, often suffers from class ...
Sandhya Ramakrishnan, L. D. Dhinesh Babu
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ShotgunWSD 2.0: An Improved Algorithm for Global Word Sense Disambiguation
IEEE Access, 2019 ShotgunWSD is a recent unsupervised and knowledge-based algorithm for global word sense disambiguation (WSD). The algorithm is inspired by the Shotgun sequencing technique, which is a broadly-used whole genome sequencing approach. ShotgunWSD performs WSD
Andrei M. Butnaru, Radu Tudor Ionescu
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Automatic Accuracy Prediction for AMR Parsing
, 2019 Meaning Representation (AMR) represents sentences as directed, acyclic and rooted graphs, aiming at capturing their meaning in a machine readable format. AMR parsing converts natural language sentences into such graphs.
Frank, Anette, Opitz, Juri
core +1 more source
Cryptocurrency Trend Prediction Through Hybrid Deep Transfer Learning
International Journal of Intelligent Systems, Volume 2025, Issue 1, 2025.The impact of sentiment analysis of comments on social networks such as X (Twitter) on the cryptocurrency market’s behavior has been proven. Also, traditional sentiment analysis and not considering the possible aspects of tweets can cause the deep model to be misleading in predicting the price trend of cryptocurrencies.
Kia Jahanbin +2 more
wiley +1 more source
SemEval 2014 Task 5 - L2 Writing Assistant [PDF]
Proceedings of the 8th International Workshop on Semantic Evaluation (SemEval 2014), 2014 We present a new cross-lingual task for SemEval concerning the translation of L1 fragments in an L2 context. The task is at the boundary of Cross-Lingual Word Sense Disambiguation and Machine Translation. It finds its application in the field of computer-assisted translation, particularly in the context of second language learning.
Gompel, M. van +4 more
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Affect detection from arabic tweets using ensemble and deep learning techniques
Journal of King Saud University: Computer and Information Sciences, 2022 Affect detection from text has captured the attention of researchers recently. This is due to the rapid use of social media sites (e.g. Twitter, Facebook), which allows users to express their feelings, emotions, and thoughts in textual format.
Omar AlZoubi +2 more
doaj
Query-Based Keyphrase Extraction from Long Documents
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022 Transformer-based architectures in natural language processing force input size limits that can be problematic when long documents need to be processed. This paper overcomes this issue for keyphrase extraction by chunking the long documents while keeping
Martin Dočekal, Pavel Smrž
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, 2017 We present our submitted systems for Semantic Textual Similarity (STS) Track 4 at SemEval-2017. Given a pair of Spanish-English sentences, each system must estimate their semantic similarity by a score between 0 and 5.
Agnes, Frederic +3 more
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