Conflict analysis for Turkish debates using text mining and text segmentation techniques

Adem Karahoca, Dilek Karahoca, Efe Buyuk
2017 Global Journal of Computer Sciences Theory and Research  
Conflict Analysis is one of the most challenging issues in the world that many organizations and governments try to carry out perfectly. It is crucial to have a correct analysis to prepare a resolution for a problem. Thus, this study paper focuses on the ways that a software program can detect the reasons of arguments in a debate. The examples of debate dialogs are chosen from Turkish language because there is not much research in this area with this language. Moreover, the techniques which are
more » ... applied in this work can also be applied to other languages, because a sentiment word dictionary is used and sentiments are almost the same in every language. This is a prepared dictionary from SentiWordNet with all the sentiment points for English words. It is translated and extended for the Turkish language. Furthermore, both machine learning and lexicon-based approaches are implemented in order to increase the diversity of results. This paper aims to show that languages can be processed in a technical manner and meanings can be extracted from sentences to understand the reasons of arguments. Likewise, the main contribution of this study is that conflict analysis for Turkish debates can be applied with the techniques which are examined here and they are also suitable for other languages.Conflict Analysis is one of the most challenging issues in the world that many organizations and governments try to carry out perfectly. It is crucial to have a correct analysis to prepare a resolution for a problem. Thus, this study paper focuses on the ways that a software program can detect the reasons of arguments in a debate. The examples of debate dialogs are chosen from Turkish language because there is not much research in this area with this language. Moreover, the techniques which are applied in this work can also be applied to other languages, because a sentiment word dictionary is used and sentiments are almost the same in every language. This is a prepared dictionary from SentiWordNet with all the sentiment points for English words. It is translated and extended for the Turkish language. Furthermore, both machine learning and lexicon-based approaches are implemented in order to increase the diversity of results. This paper aims to show that languages can be processed in a technical manner and meanings can be extracted from sentences to understand the reasons of arguments. Likewise, the main contribution of this study is that conflict analysis for Turkish debates can be applied with the techniques which are examined here and they are also suitable for other languages.
doi:10.18844/gjcs.v6i2.1651 fatcat:g5zqdviwvfhuxbyluh6umcbiy4