2017
DOI: 10.1007/s42001-017-0002-9
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From neuroscience to computer science: a topical approach on Twitter

Abstract: Twitter is perhaps the most influential microblogging service, with 271 million regular users producing approximately 500 million tweets per day. Previous studies of tweets discussing scientific topics are limited to local surveys or may not be representative geographically. This indicates a need to harvest and analyse tweets with the aim of understanding the level of dissemination of science related topics worldwide. In this study, we use Twitter as case of study and explore the hypothesis of science populari… Show more

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Cited by 7 publications
(3 citation statements)
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“…Algorithms were implemented in order to manipulate data in PHP language and a PostgreSQL data management system was used for storing and retrieving information. This system has been tested in other contexts such as the analysis of tweets and journalistic texts (Piña et al 2018 ). The methodology can be described as follows: Selection.…”
Section: Analysis Of Vallarta’s Scientific Production Abstracts (1924...mentioning
confidence: 99%
“…Algorithms were implemented in order to manipulate data in PHP language and a PostgreSQL data management system was used for storing and retrieving information. This system has been tested in other contexts such as the analysis of tweets and journalistic texts (Piña et al 2018 ). The methodology can be described as follows: Selection.…”
Section: Analysis Of Vallarta’s Scientific Production Abstracts (1924...mentioning
confidence: 99%
“…Although until now most social research using UGC has focused on analyzing Twitter and Facebook data (e.g. [1,32,41,42]), user generate content can be found across different types of outlets, including posts on online forums, customer reviews, newspaper comments, and interaction on social media.…”
Section: User-generated Online Datamentioning
confidence: 99%
“…The recent availability of large datasets on language, music, and other cultural constructs has allowed the study of human culture at a level never possible before, opening the data-driven field of culturomics (Lieberman et al, 2007;Michel et al, 2011;Dodds et al, 2011;Serrà et al, 2012;Blumm et al, 2012;Solé et al, 2013;Tadić et al, 2013;Gerlach and Altmann, 2013;Perc, 2013;Febres et al, 2015;Wagner et al, 2014;Piña-Garcia et al, 2016;Piña-García et al, 2018). In the social sciences and humanities, lack of data has traditionally made it difficult or even impossible to contrast and falsify theories of social behaviour and cultural evolution.…”
Section: Introductionmentioning
confidence: 99%