Técnicas big data: Análisis de textos a gran escala para la investigación científica y periodística

Carlos Arcila-Calderón; Eduar Barbosa-Caro; Francisco Cabezuelo-Lorenzo

doi:10.3145/epi.2016.jul.12

Técnicas big data: Análisis de textos a gran escala para la investigación científica y periodística

Translated title of the contribution: Big data techniques: Large-scale text analysis for scientific and journalistic research

Carlos Arcila-Calderón, Eduar Barbosa-Caro, Francisco Cabezuelo-Lorenzo

Research output: Contribution to journal › Article › peer-review

38 Scopus citations

Abstract

This paper conceptualizes the term big data and describes its relevance in social research and journalistic practices. We explain large-scale text analysis techniques such as automated content analysis, data mining, machine learning, topic modeling, and sentiment analysis, which may help scientific discovery in social sciences and news production in journalism. We explain the required e-infrastructure for big data analysis with the use of cloud computing and we asses the use of the main packages and libraries for information retrieval and analysis in commercial software and programming languages such as Python or R.

Translated title of the contribution	Big data techniques: Large-scale text analysis for scientific and journalistic research
Original language	Spanish
Pages (from-to)	623-631
Number of pages	9
Journal	Profesional de la Informacion
Volume	25
Issue number	4
DOIs	https://doi.org/10.3145/epi.2016.jul.12
State	Published - 2016
Externally published	Yes

All Science Journal Classification (ASJC) codes

Communication
Library and Information Sciences

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10.3145/epi.2016.jul.12

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AU - Cabezuelo-Lorenzo, Francisco

PY - 2016

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AB - This paper conceptualizes the term big data and describes its relevance in social research and journalistic practices. We explain large-scale text analysis techniques such as automated content analysis, data mining, machine learning, topic modeling, and sentiment analysis, which may help scientific discovery in social sciences and news production in journalism. We explain the required e-infrastructure for big data analysis with the use of cloud computing and we asses the use of the main packages and libraries for information retrieval and analysis in commercial software and programming languages such as Python or R.

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Técnicas big data: Análisis de textos a gran escala para la investigación científica y periodística

Abstract

All Science Journal Classification (ASJC) codes

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