CALL FOR PAPERS: Computational Methods and Big Data in Communication Research - AMIC, Asociación Mexicana de Investigadores de la Comunicación


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Asociación Mexicana de Investigadores de la Comunicación, AMIC

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CALL FOR PAPERS: Computational Methods and Big Data in Communication Research

Dear researchers:


We are announcing the call for papers for the next issue of (indexed in SCOPUS, ESCI and SciELO Citation Index, among others), which will be published in December 2020 and will include a thematic section on Computational methods and Big Data in communication research. The final deadline for receiving manuscripts is June 30, 2020. Professors Carlos Arcila Calderón (University of Salamanca), Wouter Van Atteveldt (VU University Amsterdam) and Damian Trilling (University of Amsterdam) are this issue’s guest editors.


We invite researchers and academics to go to to access all the details about this Call for papers (also included at the end of this mail) and to read our last issue, No. 45, published last December, which showcases 14 works by leading authors.


Best regards,

Sebastián Valenzuela, Editor in Chief (

Daniela Grassau, Managing Editor (


School of Communications

Pontificia Universidad Católica de Chile

+56 2 2354 2949


CALL FOR PAPERS: Computational Methods and Big Data in Communication Research


Deadline for submissions: June 30, 2020


The increasing amount of social data and the recent incorporation of computational methods into social sciences and humanities are prompting communication research to include novel approaches to study media and communication practices. In this special issue, we invite authors to send proposals that reflect empirical and theoretical work using computational methods that surpass or complement traditional methods applied to communication research. Computational methods might be used to manage both small and big data problems with special interest in the application of machine learning approaches to structured and unstructured data. Special attention will be paid to text analytics, text mining, sentiment analysis and topic modeling to media content, social media posts or other types of texts that are relevant to communication research. Advanced visualization and studies in data journalism will be considered as well.  We also welcome research derived from social network and semantic network analysis, as well as agent-based modeling, experimental and simulation research. Papers should include a theoretical discussion of how these methods are transforming the questions, hypotheses and results in our field.


The current body of literature in the nascent field of computational communication research includes comparatively little work in languages other than English, and suffers from a heavy under-representation of many countries. We especially call for contributions that broaden this scope in terms of languages and/or geographical regions.


We suggest the following topics:


- Big data analytics in communication research


- Supervised and unsupervised machine learning approaches in communication research


- The application of text analytics, text mining, sentiment analysis and topic modeling to media contents, social media posts or other types of relevant texts in communication research


- Online experiments, simulation and agent-based modeling applied to media and communication research


- Social network analysis and semantic network analysis


- Digital traces, visualization and data journalism studies


Other topics not included in the above list might also be considered. We specially encourage authors working in/about the Global South to send proposals. Papers might also include/refer to code or technical platforms in order to replicate their methods. All works must comply with the style standards published in the manual of the American Psychological Association (APA) (6th edition). Please, review the "Rules for authors" of the journal.


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