Abstract
One of the main objectives of having securities stock markets is to ensure fair trading. Our analysis of this study will show how sentiment analysis and text mining techniques can help stock markets to sense wipes in the market participants' behaviors and how the market community can benefit from it. The ability to detect potential insiders and investors' mood would help the stock market to take necessary actions to protect the trading environment and enhance investors’ trust in the market. In this project, we will be building a pilot proof of concept utilizing sentiment analysis on Twitter, one of the most popular social media applications, and Dubai Financial Market, one of the most active stock markets in the United Arab Emirates (UAE), in the English language. The project can grow in sophistication and coverage in the future. In this project, I am using R as a primary development tool where a statistical and visual analysis will be carried out utilizing its rich open community libraries.
Publication Date
5-12-2020
Document Type
Master's Project
Student Type
Graduate
Degree Name
Professional Studies (MS)
Department, Program, or Center
Graduate Programs & Research (Dubai)
Advisor
Sanjay Modak
Advisor/Committee Member
Ioannis Karamitsos
Recommended Citation
Hawas, Khaled Fawzi, "Impact of Social Media on Dubai Stock Market using Sentiment Analysis" (2020). Thesis. Rochester Institute of Technology. Accessed from
https://repository.rit.edu/theses/10691
Campus
RIT Dubai
