ISSS608 2016 17T1 Group4 Proposal
| PROPOSAL | POSTER | APPLICATION | REPORT |
Motivation
The volume and text rich tweet information is not useful unless analyzed, to give actionable insights. This information is vital to stakeholders who want to know their current status and the trend. For instance on the day of 2016 US presidential election, Twitter proved to be the largest source of breaking news with 40 million tweets. The resulting story from the analysis of Twitter user community can explain the past and the course of action to change directions in the future.
Background
Twitter is described as the SMS of the internet. When key events occur, knowing the buzz from an information network such as Twitter tells you the present. Our aim is to visually analyze the association of #tags, representing a key idea, with @mentions. We build an interactive application with R-Shiny which allows us to explore and identify the connections within the network. The interactive features of some R packages are also exhibited through this application.
Data Source
Downloaded 19K tweets from www.followthehashtag.com for popular US election #tags.
Challenges
- Identifying appropriate tools and sources for tweets data collection
- Mining and preparing the voluminous tweets data into a usable format for analysis
- Transforming the unstructured network information to a structured data with defined nodes, links and weights to be able to represent a network graph
- Identify the appropriate packages in R that can enable interactive network graph visualizations.
