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Collect tweets or social media posts related to a specific topic or hashtag, and analyze the sentiment of the posts (positive, negative, or neutral) using Natural Language Processing (NLP) techniques …
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### Description:
Perform comprehensive exploratory data analysis (EDA) on the Sentiment140 dataset to gain insights into the data and identify patterns. The following analyses should be included:…
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Here is a simple Naive Bayes test data
# positive or negative, whether it contains word a1, wether it contains word a2, ....
0,1 0 0
0,1 0 0
1,0 1 0
1,0 1 0
So we need to have
1. Find a list of impo…
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1. Simple linear classifier: Uses the weights of the words derived from (SentiWordNet + Synonyms) to classify the tweets as positive or negative.
Example:
tweet: happy cake
it averages the p…
omna updated
11 years ago
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### Description
twitter-sentiment is currently using textBlob default ML algorithm. To develop our own 'custom' ML algorithm, we need to develop a training dataset labeling each Tweet as positive or …
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**Stock Sentiment Analyzer**
**Backend**: Java pulls in real-time financial news or social media data related to specific stocks and runs sentiment analysis using an algorithm (positive, neutral, n…
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- After fitting classifier on 80%
- for each user in remaining 20%
- generate feature vectors for all tweets up to protest tweet
(e.g., tweet 1, tweet 1-2, tweet 1-3,...)
- Use classif…
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Check what threshold will yield reasonable percentage of positive/negative tweets. Graph of mean objectivity versus threshold versus number of thrown-out tweets. What precisely is objectivity - how te…
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This project conducts a comprehensive analysis of Twitter data, encompassing data preprocessing, sentiment analysis, user categorization and machine learning modeling. It begins by cleaning and prepar…
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Add a section that embeds a selection of tweets. Primary use case would be to highlight tweets that share positive experiences at past events.
https://www.npmjs.com/package/twitter-status would mak…