Member:Yixuan Zhao Alaa Ayach
The Walking Dead is a show tells the story of a small group of survivors living in the aftermath of a zombie apocalypse. As The Walking Dead becomes more and more popular, we came up with an idea to analysis the tweets in sentiments analysis and gender predication by using machine learning techniques and to show whether they have relationship between these two aspects. Also, by using different parameters, we curious whether different machine learning method will effect the accuracies.
Sentiments analysis is becoming one of the most profound research areas for prediction and classification. Automated sentiment analysis of text is used in fields where products and services are reviewed by customers and critics. Here we use different machine learning models to predict the sentiments of the tweets and compare the accuracies.
Also gender prediction always be focused in different fields. Here we use different machine learning models to predict the gender of users. At last, we combine these two parts and get the distribution of different sentiments with different genders.
In our project, we have two assumptions. First, we assume that people who post the tweets are watching or watched the tv show The Walking Dead. Second, we assume that the sentiments of the tweets people post are their truly feeling. They doesn’t post fake feeling tweets.
Yixuan Zhao: collect data, processing data, sentiment analysis, gender prediction, ppt, report Alaa Ayach: collect data, R code programming, ppt
CS 579.pdf The original proposal pdf. twitter1.cfg Configuration file of twitter API. report.pdf The report of the project. presentation.pdf The presentation pdf. cs579project.ipynb The code of this project. picture Store all the picture show in the presentation.
The pickle file here store the data after filter and processing. You can get the result directly from the pickle file.