Online social communities are an invaluable avenue for understanding user emotions.
Our collaborative innovation network (CoIN) describes the attempt to find methods suitable for measuring user emotions through sentiment analysis of online data. Our aim was to develop a methodology that could help companies use customer reviews and posts from social media platforms to spot insights for improving product strategy and thus performance.
In order to conduct the analysis of the data, we tested a number of social network data gathering and sentiment analysis tools to be able to choose the few that were the most suitable for measuring emotions. During testing, we quickly saw the shortcomings of the quantitative sentiment analysis tools and therefore searched for sentiment analysis tools that would analyze qualitative data in order to capture the full meaning of each review and post.
The findings developed into new opportunities specifically for Citrix’s GoToMeeting product team, but can potentially be expanded to other companies using social network analysis and sentiment analysis on their customers’ online reviews and posts to understand and process their information.
To read more about the process and findings:
Bhavika Shah and Priscila Mendoza, Yulia Tammisto, Emanuel Castillo
Data collection of website comments; data analysis using the tool Condor; sentiment analysis using the following tools: IBM Many Eyes, Lexalytics, Wordle, and Linguistic Inquiry and Word Count; analysis of findings using ACCID test; writing/editing paper.
The paper and presentation was accepted for interactive poster presentation at COINs15 conference in Japan. To learn more please click here: http://www.coinsconference.org/