Characterizing documents about colombian indigenous peoples using text analytics (2020)
The indigenous peoples of Colombia have a considerable social, political and cultural wealth. However, issues such as the decadeslong armed conflict and drug trafficking have posed a significant threat to their survival. In this work, publically available documents on the Internet with information about two indigenous communities, the Aw´a and Inga people from the Cauca region in southern Colombia, are analyzed using automated text analytics approaches. A corpus is constructed comprising general characterization documents, media articles and sentences from the Constitutional Court. Topic analysis is carried out to identify the relevant themes in the corpus to characterize each community. Sentiment analysis carried out on the media articles indicates that the articles about the Inga tend to be more positive and objective than the Aw´a. This may be attributed to the significant impact that the armed conflict has had on the Awa´ in recent years, and the productive projects of the Inga. Furthermore, an approach for summarizing long, complex documents by means of timelines is illustrated with a sentence issued by the Constitutional Court. It is concluded that such an approach has significant potential to facilitate understanding of documents of this nature.