Name
Abstract | ||
|---|---|---|
User-generated content on social media sites such as Twitter and Facebook provides opportunity for researchers in various fields to understand human behaviors and social phenomena. On the one hand, these human behaviors and social phenomena are very complex in nature thus require in-depth qualitative analysis. On the other, the magnitude of social media data requires large-scale data analysis techniques. In this paper, we propose a web-based tool named SWAB (Social Web Analysis Buddy) that integrates both qualitative analysis and large-scale data mining techniques. Specifically, this tool supports asynchronous collaboration among researchers conducting inductive content analysis on textural data from users' online posts and conversations. It then aggregates the results and calculates the agreement among researchers, and builds modeling algorithms based on the qualitative results to classify large-scale social media text content. This current paper focuses on the overall workflow and user interface design of this tool. We demonstrate the prototype of this tool by analyzing student-posted content on Twitter. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/CGC.2013.67 | CGC |
Keywords | Field | DocType |
large-scale data analysis technique,large-scale social media text,social media analytics,social media sites,user interfaces,human computer interaction,social phenomenon,large-scale social media text content,web-based tool,inductive content analysis,user-generated content,student-posted content,twitter,data analysis,large-scale data mining technique,textual content analysis,facebook,social web analysis buddy,in-depth qualitative analysis,social media site,collaborative social media data,user interface design,social media data,data mining techniques,collaborative social media data analysis,internet,human behavior,swab,human behaviors,data mining,social networking (online),large-scale data analysis techniques,text mining,social phenomena | Social media analytics,World Wide Web,Content analysis,Social media,Social web,Computer science,Human behavior,Web application,User interface design,The Internet | Conference |
Citations | PageRank | References |
3 | 0.44 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chen Xin | 1 | 625 | 120.92 |
| Krishna Madhavan | 2 | 13 | 3.08 |
| Mihaela Vorvoreanu | 3 | 25 | 5.25 |