The team, from Loughborough University, say it can scan up to 2,000 tweets a second and rate them for expressions of one of eight human emotions…
The team, from the university’s new Centre for Information Management, say the system can extract a direct expression of anger, disgust, fear, happiness, sadness, surprise, shame and confusion from each tweet.
The academics said that using the Emotive software to geographically evaluate any mass mood could help police to track potential criminal behaviour or threats to public safety.
It may be able to guide national policy on the best way to react to major incidents, they added.
There have been several projects like this in recent years. The algorithms to sort out all of the language must be intricate. But, I’m skeptical about two things. One is a sampling issue. Just how many people in England are using Twitter? In the United States, the figures about regular Twitter users are still quite low. You can map the moods of Twitter users but this doesn’t necessarily represent the larger population. The Twitter population probably trends younger. At the same time, responding to vocal responses on the web or on Twitter might be effective for public relations. A second issue is how exactly tracking moods could be used to help police. So police will be sent to places that show high concentrations of disgust or anger and pay less attention to places experiencing happiness? Or, such a system might alert police to trouble spots? I suspect it is more complicated than this yet I imagine such talk could make Twitter users nervous about how exactly their moods will be analyzed.