Version:
1.0
Release Date:
January 29, 2021
Last Updated:
January 28, 2021
Authors:
Yasmine Ali, Ruth Schmidt, Tyler Price, Syed Ahmed
Editors:
Campbell Leckie, Roy Ceyleon, Mohsin Malik
StockEye provides a streamlined web-based platform for investors and market enthusiasts to view the prospective performance of popular stocks based on Twitter sentiment analysis.
Stockeye is a web application that aggregates and analyses tweets that are related to the market from the popular social networking service Twitter, offering information regarding the public sentiments of stocks to its users. StockEye allows its users to create an account and presents them with a customizable watch list of stocks, enabling them to conveniently track the sentiments of multiple stocks of their choosing. StockEye also provides users the ability to view tweets that are relevant to trending stocks. StockEye is thus intended to be another tool in an investor’s repertoire for market research.
StockEye’s user interface consists of a home page, and a personalized user page viewable by each respective user in the event that they have created an account and signed-in.
The home page displays the sentiments of popular stocks, and if the user desires, the tweets relevant to these stocks, which can be filtered through parameters, such as date posted and traction (e.g. number of retweets, number of followers of the person posting the tweet). The home page will also contain information about StockEye, its functionality, and a login box.
Each user’s personal page will consist of a watchlist of stocks of their choosing with the ability to add and remove stocks from this list. This page will also display the sentiment towards each stock and tweets relevant to these stocks (filtered as mentioned in the paragraph above).
The user base StockEye intends to serve are people who seek a convenient and efficient way to collect information concerning the stocks they are curious about, or plan to invest in. Users are thus largely expected to range from beginners to financial experts.
StockEye seeks to serve its audience in multiple ways. For one, using Twitter as a source of data is valuable due to the impact that public opinion has on the market. This enables users to make more informed investment decisions. Additionally, this platform will save users valuable time, as they will no longer be required to research and analyse Twitter sentiments themselves. As a web application StockEye is also highly accessible.
StockEye must be fully documented and implemented by April 12th, and so time is a chief constraint.
Machine learning is a key component of sentiment analysis, and the development team, as a whole, is largely unacquainted with its mechanism and details. Thus, it is expected that more time than ideal will be allocated to gathering and learning the prerequisites of machine learning demanded by the application. This is the primary obstruction in our objective to have a fully-functional implementation by the deadline.
Due to the COVID-19 pandemic, the team will be unable to coordinate in-person meetings, which could result in a reduction in productivity and clarity of communication.
The project will have no expenses, due to the usage of free services during production of the application (django, python, etc). As such, the budget for this project is 0 dollars.
Users will be required to have access to the internet in order to access StockEye. Due to StockEye being entirely web-based, the user operating system is irrelevant.