RT Journal Article
T1 Hybrid intelligence strategies for identifying, classifying and analyzing political bots
A1 García Orosa, Berta
A1 Gamallo Otero, Pablo
A1 Martín Rodilla, Patricia
A1 Martínez Castaño, Rodrigo
K1 Bots
K1 Framing
K1 Hybrid intelligence
K1 Empowerment
K1 Social media
AB Political bots, through astroturfing and other strategies, have become important players in recent elections in several countries. This study aims to provide researchers and the citizenry with the necessary knowledge to design strategies to identify bots and counteract what international organizations have deemed bots’ harmful effects on democracy and, simultaneously, improve automatic detection of them. This study is based on two innovative methodological approaches: (1) dealing with bots using hybrid intelligence (HI), a multidisciplinary perspective that combines artificial intelligence (AI), natural language processing, political science, and communication science, and (2) applying framing theory to political bots. This paper contributes to the literature in the field by (a) applying framing to the analysis of political bots, (b) defining characteristics to identify signs of automation in Spanish, (c) building a Spanish-language bot database, (d) developing a specific classifier for Spanish-language accounts, (e) using HI to detect bots, and (f) developing tools that enable the everyday citizen to identify political bots through framing
PB MDPI
YR 2021
FD 2021-09-27
LK https://hdl.handle.net/10347/37556
UL https://hdl.handle.net/10347/37556
LA eng
NO García-Orosa B., Gamallo P., Martín-Rodilla P. & Martínez-Castaño R. (2021). Hybrid Intelligence Strategies for Identifying, Classifying and Analyzing Political Bots. Social Sciences; 10(10), 357. https://doi.org/10.3390/socsci10100357
NO This article has been developed within the research project “Digital Native Media in Spain: Storytelling Formats and Mobile Strategy” (RTI2018–093346-B-C33) funded by the Ministry of Science, Innovation, and Universities and co-funded by the European Regional Development Fund (ERDF) and has received financial support from DOMINO project (PGC2018-102041-B-I00, MCIU/AEI/FEDER, UE), eRisk project (RTI2018-093336-B-C21), the Consellería de Cultura, Educación e Ordenación Universitaria (accreditation 2016–2019, ED431G/08, Groups of Reference: ED431C 2020/21, and ERDF 2014-2020: Call ED431G 2019/04) and the European Regional Development Fund (ERDF)
DS Minerva
RD 24 abr 2026