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A conceptual architecture for content analysis about abortion using the twitter platform

Abstract:

This paper presents a conceptual architecture for content analysis about the opinions expressed on Twitter about abortion. The architecture consisted of five stages: authentication, data collection, data cleaning & processing, modeling & analysis, and presentation of results. In the data collection, a simple size of tweets sent from Ecuador was taken in 2018. All tweets that were not related to the topic were eliminated. In the modeling, it was separated into two categories for and against abortion, where the Naive Bayes and decision tree classifiers were used. Finally, the results were presented in the form of statistical graphs, word clouds and heat maps. During the development, the Google maps platform was also used, where the scripts were made in Python using the Integrated Development Environment (IDE) Spyder (Python 3.6), which is part of the Anaconda platform. The results obtained showed, on average, a majority position against abortion in Ecuador.