Results 111 to 120 of about 15,951 (231)

Sarcasm Detection in Sentiment Analysis Using Recurrent Neural Networks

International Journal of Distributed Sensor Networks, Volume 2025, Issue 1, 2025.
In recent years, online opinionated textual data volume has surged, necessitating automated analysis to extract valuable insights. Data mining and sentiment analysis have become essential for analysing this type of text. Sentiment analysis is a text classification problem associated with many challenges, including better data preprocessing and sarcasm ...
Maneeha Rani, Muhammad Babar, Syed Zafar Ali Shah, Ali Abbas, Muhammad Sohail Hayat, Shafiq Ahmad, Sadaqat Jan, Rahul Priyadarshi   +7 more
wiley   +1 more source

Robust Incremental Neural Semantic Graph Parsing

, 2017
Parsing sentences to linguistically-expressive semantic representations is a key goal of Natural Language Processing. Yet statistical parsing has focused almost exclusively on bilexical dependencies or domain-specific logical forms.
Blunsom, Phil, Buys, Jan
core   +1 more source

Sentiment Analysis in Twitter: A SemEval Perspective [PDF]

Proceedings of the 7th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, 2016
The recent rise of social media has greatly democratized content creation. Facebook, Twitter, Skype, Whatsapp and LiveJournal are now commonly used to share thoughts and opinions about anything in the surrounding world. This proliferation of social media content has created new opportunities to study public opinion, with Twitter being especially ...
openaire   +1 more source

SemEval-2013 Task 5: Evaluating Phrasal Semantics [PDF]

, 2013
This paper describes the SemEval-2013 Task 5: “Evaluating Phrasal Semantics”. Its first subtask is about computing the semantic similarity of words and compositional phrases of minimal length. The second one addresses deciding the compositionality of phrases in a given context.
Korkontzelos, I, Zesch, T, ZANZOTTO, FABIO MASSIMO, Biemann, C.   +3 more
openaire   +3 more sources

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, Marton Gergely, Khaled Shuaib, Mahmaod Alrawad   +3 more
wiley   +1 more source

SemEval-2016 Task 6: Detecting Stance in Tweets [PDF]

Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016), 2016
10th International Workshop on Semantic Evaluation (SemEval-2016), 16-17 June 2016, San Diego, California ...
Parinaz Sobhani, Svetlana Kiritchenko, Xiaodan Zhu, Colin Cherry, Saif M. Mohammad   +4 more
openaire   +2 more sources

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, Mohammad Ali Zare Chahooki, Gianni Costa   +2 more
wiley   +1 more source

SemEval-2023 Task 9: Multilingual Tweet Intimacy Analysis [PDF]

, 2023
Jiaxin Pei, Vítor Silva, Maarten W. Bos, Yozen Liu, Leonardo Neves, David Jurgens, Francesco Barbieri   +6 more
openalex   +1 more source

Artificial Intelligence for Text Analysis in the Arabic and Related Middle Eastern Languages: Progress, Trends, and Future Recommendations

International Journal of Intelligent Systems, Volume 2025, Issue 1, 2025.
In the last 10 years, there has been a rise in the number of Arabic texts, which necessitates a more profound understanding of algorithms to efficiently understand and classify Arabic texts in many applications, like sentiment analysis. This paper presents a comprehensive review of recent developments in Arabic text classification (ATC) and Arabic text
Abdullah Y. Muaad, Md Belal Bin Heyat, Faijan Akhtar, Usman Naseem, Wadeea R. Naji, Suresha Mallappa, Hanumanthappa J., Mohamadreza (Mohammad) Khosravi   +7 more
wiley   +1 more source

Learning for clinical named entity recognition without manual annotations

Informatics in Medicine Unlocked, 2018
Background: Named entity recognition (NER) systems are commonly built using supervised methods that use machine learning to learn from corpora manually annotated with named entities.
Omid Ghiasvand, Rohit J. Kate
doaj   +1 more source