vivekn/sentiment
Sentiment analysis using machine learning techniques. (⭐ 496)
Sentiment analysis using machine learning techniques. (⭐ 496)
Sentiment, sentimentality are terms for sensitiveness to emotional feelings. Sentiment is a sincere and refined sensibility, a tendency to be influenced by emotion rather than reason or fact: to appeal …
AFINN-based sentiment analysis for Node.js. (⭐ 2676)
We present the Newspaper Bias Dataset (NewB), a text corpus of more than 200,000 sentences from eleven news sources regarding Donald Trump. While previous datasets have labeled sentences as either liberal or conservative, NewB covers the political vi...
We present the first Africentric SemEval Shared task, Sentiment Analysis for African Languages (AfriSenti-SemEval) - The dataset is available at https://github.com/afrisenti-semeval/afrisent-semeval-2023. AfriSenti-SemEval is a sentiment classificati...
Sentiment analysis can aid in understanding people's opinions and emotions on social issues. In multilingual communities sentiment analysis systems can be used to quickly identify social challenges in social media posts, enabling government departmen...
In online social networks people often express attitudes towards others, which forms massive sentiment links among users. Predicting the sign of sentiment links is a fundamental task in many areas such as personal advertising and public opinion analy...
In sentiment analysis of longer texts, there may be a variety of topics discussed, of entities mentioned, and of sentiments expressed regarding each entity. We find a lack of studies exploring how such texts express their sentiment towards each entit...
In this paper, we describe the 2015 iteration of the SemEval shared task on Sentiment Analysis in Twitter. This was the most popular sentiment analysis shared task to date with more than 40 teams participating in each of the last three years. This ye...
Sentence2vec by Rock (⭐ 311)
In NLP, a large volume of tasks involve pairwise comparison between two sequences (e.g. sentence similarity and paraphrase identification). Predominantly, two formulations are used for sentence-pair tasks: bi-encoders and cross-encoders. Bi-encoders...
Over the recent decades, there has been a significant increase and development of resources for Arabic natural language processing. This includes the task of exploring Arabic Language Sentiment Analysis (ALSA) from Arabic utterances in both Modern St...
Sentiment Analysis Adapter trained on the Yahoo Movie Review dataset by Bandai Namco Research Inc. (⭐ 10)
Using NLP and LDA for Topic Modeling and Sentiment Analysis (⭐ 43)
Sentinel policies for use in pre-sales workshops: https://hashicorp.github.io/workshops (⭐ 26)
After the first 500 resumes were sent out I made sure to check my inbox, and junk email and my phone and that its all working properly and nothing is being blocked or sent elsewhere. 5000 Resumes. ...
SentimentAnalysis_CentraleMRS25 (⭐ 13)
Let G be a context-free grammar with a total alphabet V, and let F be a final language over an alphabet W such that W is a subset of V. A final sentential form is any sentential form of G that, after omitting symbols from V - W, it belongs to F. The...
This report explores the use of paragraph break probability estimates to help predict the location of sentence breaks in English natural language text. We show that a sentence break predictor based almost solely on paragraph break probability estimat...
We report results of a longitudinal sentiment classification of Reddit posts written by students of four major Canadian universities. We work with the texts of the posts, concentrating on the years 2020-2023. By finely tuning a sentiment threshold to...