For local governments, there are many different situations where text mining could be useful. A lot of different informational updates are now posted on different social media outlets. Each of these outlets get a variety of comments from citizens. Text mining could be useful to gauge sentiment across multiple platforms to see if a specific information release was received positively or not, and if there are any trends within the responses.
A lot of different government work also includes the need to go through public comment periods for things like regulatory changes, legislation changes, and environmental impact analyses. In times where the quantity of responses is very large, it would be very helpful to perform text mining on all the responses to see the sentiment and key discussion points that are most discussed. For planning purposes, it would also be useful to perform text mining on different social media posts in general to gauge what people are talking about positively and increase those factors around the city. Conversely, it would be useful to find out what items in the community receive the most negative sentiment and actively work towards mitigating those issues. For many of these items, it not only increases understanding and insight to enable better resource use, but it can also increase the social equity aspect of community engagement. Not all citizens are able to attend public meetings during work hours or have the time to write in comments on regulation. However, text mining would enable anybody’s comments across internet platforms to be heard without bias. In these ways, text mining could help reduce costs from implementing unwanted projects and increase citizen happiness and participation.
Author: Logan Callen
Provost, Foster and Tom Fawcett. 2013. Data Science for Business. 2nd Edition. California: O’Reilly Media, Inc.