Bot crawler to retrieve data from Facebook based on the selection of posts and the extraction of user profiles

Introduction— Data can currently be found within organizations and outside of them, they are growing exponentially. Today, the information available on the Internet and social networks has become a generator of value, through the effective analysis of a specific situation, using techniques and metho...

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Vydané v:Inge Cuc Ročník 18; číslo 2; s. 101 - 113
Hlavní autori: Sánchez Paipilla, Ariel Guillermo, Durán Vaca, Mónica Katherine, Ballesteros Ricaurte, Javier Antonio, González Amarillo, Angela María, López, Pedro Nel
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: 20.09.2022
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ISSN:0122-6517, 2382-4700, 2382-4700
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Shrnutí:Introduction— Data can currently be found within organizations and outside of them, they are growing exponentially. Today, the information available on the Internet and social networks has become a generator of value, through the effective analysis of a specific situation, using techniques and methodologies with which content-based solutions can be proposed, and thus achieve, execute timely, intelligent and assertive decision-making processes. Objective— The main objective of this work is to development of a Bot Crawler, which allows extracting information from Facebook without access restrictions, or request for credentials, based on web crawling and scraping techniques, through the selection of HTML tags, to track and be able to define patterns. Methodology— The development of this project consisted of four main stages: A) Teamwork with SCRUM, B) Comparison of web data extraction techniques, C) Extraction and validation of permissions to access the data in Facebook, D) Development of the bor crawler. Results— As a result of this process, a graphical interface was created to review the process of obtaining data derived from user profiles in this social network. Conclusions— As a result of this process, a graphical interface is created that allows checking the process of obtaining data derived from user profiles of this social network.
ISSN:0122-6517
2382-4700
2382-4700
DOI:10.17981/ingecuc.18.2.2022.08