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SecLists/Discovery/Web-Content/raft-small-words.txt at master · danielmiessler/SecLists · GitHub
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C++ interface between SISTA's CoreNLP processors and SwiRL. - SwiRL-NLP/model_swirl/lemma.counts at master · trananh/SwiRL-NLP
SwiRL-NLP/model_swirl/lemma.counts at master · trananh/SwiRL-NLP · GitHub
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This project addresses the problem of sentiment analysis on Twitter. The goal of this project was to predict sentiment for the given Twitter post using Python. Sentiment analysis can predict many different emotions attached to the text, but in this report, only 3 major were considered: positive, negative and neutral. The training dataset was small (just over 5900 examples) and the data within it was highly skewed, which greatly impacted on the difficulty of building a good classifier. After creating a lot of custom features, utilizing bag-of-words representations and applying the Extreme Gradient Boosting algorithm, the classification accuracy at the level of 58% was achieved. Analysing the public sentiment as firms trying to find out the response of their products in the market, predicting political elections and predicting socioeconomic phenomena like the stock exchange. - Sentiment-Analysis-of-Text-Data-Tweets-/data/train.csv at master · ajayshewale/Sentiment-Analysis-of-Text-Data-Tweets
Sentiment-Analysis-of-Text-Data-Tweets-/data/train.csv at master · ajayshewale/Sentiment-Analysis-of-Text-Data-Tweets- · GitHub
An English version of the context based spell checker Valkuil.net. - fowlt/servers/timblservers/they're,their,there.IGTree at master · Woseseltops/fowlt
fowlt/servers/timblservers/they're,their,there.IGTree at master · Woseseltops/fowlt · GitHub
Twitter sentiment analysis with WEKA. Contribute to egidisa/Sentweet development by creating an account on GitHub.
Sentweet/testTweets10000pos.arff at master · egidisa/Sentweet · GitHub