Are opinions expressed in land-use planning documents?

Abstract

A great deal of research on information extraction from textual datasets has been performed in specific data contexts, such as movie reviews, commercial product evaluations, campaign speeches, etc. In this paper, we raise the question on how appropriate these methods are for documents related to land-use planning. The kind of information sought concerns the stakeholders, sentiments, geographic information, and everything else related to the territory. However, it is extremely challenging to link sentiments to the three dimensions that constitute geographic information (location, time, and theme). After highlighting the limitations of existing proposals and discussing issues related to textual data, we present a method called OPILAND (OPinion mIning from LAND-use planning documents) designed to semi-automatically mine opinions related to named-entities in specialized contexts. Experiments are conducted on a Thau lagoon dataset (France), and then applied on three datasets that are related to different areas in order to highlight the relevance and the broader applications of our proposal.

Keywords:

• land-use planning
• opinion mining
• natural language processing
• geographic information retrieval
• spatial feature

Acknowledgments

The authors thank Pierre Maurel (IRSTEA – UMR TETIS, France) for its expertise on the corpus, Cedric Lopez (Viseo, France) and Sabiha Tahrat (LIRMM, France) for their participation to this work. This work was partially funded by the labex NUMEV and the Maison des Sciences de l’Homme de Montpellier (MSH-M, France).

Notes

1. http://www.linguastream.org/

2. http://www.wjh.harvard.edu/~inquirer/

3. http://www.liwc.net/

4. http://www.jeuxdemots.org/likeit.php

5. http://www.cs.waikato.ac.nz/ml/weka/

6. A larger amplitude by weighting the scores from 0 to 10 was not experimentally relevant.