what can we learn from sentiment analysis?
DESCRIPTION
A short presentation about sentiment analysis from October 13, 2009. I will update the .ppt soon to make it flow better as a slideshow for reading as opposed to supplementing a presentation. I also have some references to add. I was just eager to add get something posted!TRANSCRIPT
What is sentiment analysis?
“…translating the vagaries of human emotion into hard data” [primarily in the online world]
Mining the web for feelings, not facts (NYT)
“…us[ing] automated tools to discern, extract and process attitudinal information found in text…”
Sentiment Analysis: Opportunities and Challenges (Grimes, 2008)
“…an attempt to automatically process and possibly learn from the universe of people’s online chatter”
(Me, 2009)
In the virtual (online) world, organizations and individuals ...have access to the universe of shared opinions
Reviews, comments, tweets, blog posts, tags
…as well as behavior(s) demonstrated by users Clicks, purchases, browsing habits, social networking
decisions (i.e. Share or not share? Follow or not follow?)
…over time, and often in real time, Archive.org, Google/Twitter trends, RSS
…in a readily analyzable format.
Academic Research (e.g., not sure of purpose)
Personal Use
Market Research/Business Intelligence
Marketing Customer satisfaction Prediction markets Economics Computational Linguistics Semantic web (incorporating “feelings” into
“meaning” – this could be big)
Powering Search Engines
Real-Time, Longitudinal Data Online
Questions to Ponder What is the relationship between what you say
online, and what you do (online and offline)?
What can be learned from data about “feelings”?
How do sentiments differ across domains?
Potential applications?
Scouting?
Reputation Management?
Evaluation/ Assessment?
(Pssst Google is getting sentimental)
BANG! Wow ‘em with a headline