Results 81 to 90 of about 15,951 (231)
Sentiment analysis in SemEval: a review of sentiment identification approaches
International Journal of Electrical and Computer Engineering (IJECE), 2023 <div class="page" title="Page 1"><div class="layoutArea"><div class="column"><div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p>ocial media platforms are becoming the foundations of social interactions including messaging and opinion expression.
Bousselham El Haddaoui +3 more
openaire +2 more sources
Expert Systems, Volume 42, Issue 7, July 2025.ABSTRACT Instant messenger Telegram has emerged as a favoured platform for far‐right activism, conspiracy theories, political propaganda, and misinformation, which has its own target audience. This study explores the application of multilingual pre‐trained language models to detect and measure toxicity in political content on Telegram channels.
Arsenii Tretiakov +3 more
wiley +1 more source
Enhanced Sentiment Intensity Regression Through LoRA Fine-Tuning on Llama 3
IEEE AccessSentiment analysis and emotion detection are critical research areas in natural language processing (NLP), offering benefits to numerous downstream tasks.
Diefan Lin, Yi Wen, Weishi Wang, Yan Su
doaj +1 more source
ADeCNN: An Improved Model for Aspect-Level Sentiment Analysis Based on Deformable CNN and Attention
IEEE Access, 2020 Aspect-level sentiment analysis aims at identifying the sentiment polarity of target in the context. In most of the previous sentiment analysis models, there usually exists the problem of insufficient extraction capability of local features and long ...
Jie Zhou, Siqi Jin, Xinli Huang
doaj +1 more source
Exploring Metaphorical Senses and Word Representations for Identifying Metonyms [PDF]
, 2015 A metonym is a word with a figurative meaning, similar to a metaphor. Because metonyms are closely related to metaphors, we apply features that are used successfully for metaphor recognition to the task of detecting metonyms. On the ACL SemEval 2007 Task
Gelernter, Judith, Zhang, Wei
core
Revisiting Recurrent Networks for Paraphrastic Sentence Embeddings
, 2017 We consider the problem of learning general-purpose, paraphrastic sentence embeddings, revisiting the setting of Wieting et al. (2016b). While they found LSTM recurrent networks to underperform word averaging, we present several developments that ...
Gimpel, Kevin, Wieting, John
core +1 more source
SemEval-2015 Task 10: Sentiment Analysis in Twitter [PDF]
Proceedings of the 9th International Workshop on Semantic Evaluation (SemEval 2015), 2015 Sentiment analysis, sentiment towards a topic, quantification, microblog sentiment analysis; Twitter opinion ...
Rosenthal, Sara +5 more
openaire +3 more sources
Extracting knowledge from customer reviews: an integrated framework for digital platform analytics
International Transactions in Operational Research, Volume 32, Issue 4, Page 2061-2086, July 2025.Abstract Online review sites play a crucial role in shaping consumer purchasing decisions, making the analysis of customer feedback essential for businesses. Given the complexity of these reviews, often including both quantitative and qualitative data, advanced analytical frameworks are necessary.
Anastasios Kyriakidis +1 more
wiley +1 more source
RPf-GCNs: reciprocal perspective driven fused GCNs for rumor detection on social media
Journal of Big DataThe earliest detection of rumors across social media is the need to the hour in present global village. User’s are seamlessly connected in an unstructured network leading to rapid flow of information.
Zafran Khan +4 more
doaj +1 more source
, 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
core +1 more source