Over a decade of social opinion mining: a systematic review
Social media popularity and importance is on the increase due to people using it for various
types of social interaction across multiple channels. This systematic review focuses on the …
types of social interaction across multiple channels. This systematic review focuses on the …
Sentiment analysis of code-mixed indian languages: An overview of sail_code-mixed shared task@ icon-2017
Sentiment analysis is essential in many real-world applications such as stance detection,
review analysis, recommendation system, and so on. Sentiment analysis becomes more …
review analysis, recommendation system, and so on. Sentiment analysis becomes more …
Transfer learning for sentiment analysis using BERT based supervised fine-tuning
The growth of the Internet has expanded the amount of data expressed by users across
multiple platforms. The availability of these different worldviews and individuals' emotions …
multiple platforms. The availability of these different worldviews and individuals' emotions …
XLM-T: Multilingual language models in Twitter for sentiment analysis and beyond
Language models are ubiquitous in current NLP, and their multilingual capacity has recently
attracted considerable attention. However, current analyses have almost exclusively focused …
attracted considerable attention. However, current analyses have almost exclusively focused …
Sentiment analysis in Tamil texts: A study on machine learning techniques and feature representation
Sentiment Analysis (SA) is an application of Natural Language Processing (NLP) to extract
the sentiments expressed in the text. In this paper, we experimented five approaches to …
the sentiments expressed in the text. In this paper, we experimented five approaches to …
A hybrid deep learning architecture for sentiment analysis
In this paper, we propose a novel hybrid deep learning archtecture which is highly efficient
for sentiment analysis in resource-poor languages. We learn sentiment embedded vectors …
for sentiment analysis in resource-poor languages. We learn sentiment embedded vectors …
An efficient hybrid filter and evolutionary wrapper approach for sentiment analysis of various topics on Twitter
Sentiment Analysis is currently considered as one of the most attractive research topics in
Natural Language Processing (NLP) field. The main objective of sentiment analysis is to …
Natural Language Processing (NLP) field. The main objective of sentiment analysis is to …
Sentiment analysis using XLM-R transformer and zero-shot transfer learning on resource-poor indian language
Sentiment analysis on social media relies on comprehending the natural language and
using a robust machine learning technique that learns multiple layers of representations or …
using a robust machine learning technique that learns multiple layers of representations or …
L3cubemahasent: A marathi tweet-based sentiment analysis dataset
A Kulkarni, M Mandhane, M Likhitkar… - arxiv preprint arxiv …, 2021 - arxiv.org
Sentiment analysis is one of the most fundamental tasks in Natural Language Processing.
Popular languages like English, Arabic, Russian, Mandarin, and also Indian languages such …
Popular languages like English, Arabic, Russian, Mandarin, and also Indian languages such …
Benchmarking multi-task learning for sentiment analysis and offensive language identification in under-resourced dravidian languages
To obtain extensive annotated data for under-resourced languages is challenging, so in this
research, we have investigated whether it is beneficial to train models using multi-task …
research, we have investigated whether it is beneficial to train models using multi-task …