Social Media Community Analysis
Under the direction of Dr. Susan Mengel (Texas Tech University), I worked on analysis of visualization of communities. In this study on the networks of two fields of topics on twitter, I will show that while communities may look very similar while browsing Twitter when the community is analyzed using different techniques they are much different. The visualization done in this experiment will provide useful tools for analyzing these communities on social media, and can help create a foundation for behavioral analysis overtime on these communities. This experiment can be adapted to many other social media sites and is not limited to twitter communities.
Primary languages used: Python, R
Social Media Community Growth Prediction
Under the Direction of Dr. Susan Mengel (Texas Tech University), I worked on an analysis of prediction techniques commonly used in social media growth prediction. In this analysis we worked to determine if these techniques could be applied to a community while maintaining accuracy. In this research 5000 posts were used per month for the political dataset. This data was used to determine the average growth rate of the community and how a single post may do based on several factors used in growth analysis, these factors include month, follower count, favorite count, and retweet count. These factors combine to provide a basis for the prediction of growth in a community based on normal growth factors. The source code of this project can be found on GitHub.
Primary languages used: Python, R
