Twitter is one of the most popular information source available on the Web. Thus, there exist many studies focused on analyzing the credibility of the shared information. Most proposals use either Twitter API or web scraping to extract the data to perform such analysis. Both extraction techniques have advantages and disadvantages. In this work, we present a study to evaluate their performance and behavior. The motivation for this research comes from the necessity to know ways to extract online information in order to analyze in real-time the credibility of the content posted on the Web. To do so, we develop a framework which offers both alternatives of data extraction and implements a previously proposed credibility model. Our framework is implemented as a Google Chrome extension able to analyze tweets in real-time. Results report that both methods produce identical credibility values, w...

This research was supported by the FONDO NACIONAL DE DESARROLLO CIENTÍFICO, TECNOLÓGICO Y DE INNOVACIÓN TECNOLÓGICA – FONDECYT as executing entity of CONCYTEC under grant agreement no. 01–2019-FONDECYT-BM-INC.INV in the project RUTAS: Robots para centros Urbanos Turísticos Autónomos y basados en Semántica.