Twitter-Sentiment-Analysis and Twitter_Sentiment_Analysis
About Twitter-Sentiment-Analysis
sharmaroshan/Twitter-Sentiment-Analysis
It is a Natural Language Processing Problem where Sentiment Analysis is done by Classifying the Positive tweets from negative tweets by machine learning models for classification, text mining, text analysis, data analysis and data visualization
This project helps social media managers or brand analysts automatically sort through tweets to identify those containing hate speech. It takes raw tweet data as input and categorizes each tweet as either 'racist/sexist' or 'not racist/sexist'. This allows users to quickly flag and address problematic content.
About Twitter_Sentiment_Analysis
dD2405/Twitter_Sentiment_Analysis
Detecting whether a particular tweet contains negative emotions attached with it or not from the given dataset
This tool helps social media managers and community moderators identify and filter out racist or sexist hate speech from Twitter feeds. You provide a dataset of tweets, and the tool classifies them, flagging those with negative, abusive sentiments. The output helps you maintain a safer, more positive online environment.
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