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A qualitative and quantitative comparison between Web scraping and API methods for Twitter credibility analysis

dc.rights.licenseopenen_US
hal.structure.identifierESTIA INSTITUTE OF TECHNOLOGY
dc.contributor.authorDONGO, Irvin
dc.contributor.authorCARDINALE, Yudith
dc.contributor.authorAGUILERA, Ana
dc.contributor.authorMARTINEZ, Fabiola
dc.contributor.authorQUINTERO, Yuni
dc.contributor.authorROBAYO, German
dc.contributor.authorCABEZA, David
dc.date.accessioned2023-04-05T08:24:53Z
dc.date.available2023-04-05T08:24:53Z
dc.date.issued2021-08-03
dc.identifier.issn1744-0084en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/172760
dc.description.abstractEnPurpose This paper aims to perform an exhaustive revision of relevant and recent related studies, which reveals that both extraction methods are currently used to analyze credibility on Twitter. Thus, there is clear evidence of the need of having different options to extract different data for this purpose. Nevertheless, none of these studies perform a comparative evaluation of both extraction techniques. Moreover, the authors extend a previous comparison, which uses a recent developed framework that offers both alternates of data extraction and implements a previously proposed credibility model, by adding a qualitative evaluation and a Twitter-Application Programming Interface (API) performance analysis from different locations. Design/methodology/approach As one of the most popular social platforms, Twitter has been the focus of recent research aimed at analyzing the credibility of the shared information. To do so, several proposals use either Twitter API or Web scraping to extract the data to perform the analysis. Qualitative and quantitative evaluations are performed to discover the advantages and disadvantages of both extraction methods. Findings The study demonstrates the differences in terms of accuracy and efficiency of both extraction methods and gives relevance to much more problems related to this area to pursue true transparency and legitimacy of information on the Web. Originality/value Results report that some Twitter attributes cannot be retrieved by Web scraping. Both methods produce identical credibility values when a robust normalization process is applied to the text (i.e. tweet). Moreover, concerning the time performance, Web scraping is faster than Twitter API and it is more flexible in terms of obtaining data; however, Web scraping is very sensitive to website changes. Additionally, the response time of the Twitter API is proportional to the distance from the central server at San Francisco.
dc.language.isoENen_US
dc.title.enA qualitative and quantitative comparison between Web scraping and API methods for Twitter credibility analysis
dc.typeArticle de revueen_US
dc.identifier.doi10.1108/IJWIS-03-2021-0037en_US
dc.subject.halInformatique [cs]en_US
bordeaux.journalInternational Journal of Web Information Systemsen_US
bordeaux.page580-606en_US
bordeaux.volume17en_US
bordeaux.hal.laboratoriesESTIA - Rechercheen_US
bordeaux.issue6en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionBordeaux INPen_US
bordeaux.institutionBordeaux Sciences Agroen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcehal
hal.identifierhal-03520067
hal.version1
hal.exportfalse
workflow.import.sourcehal
dc.rights.ccPas de Licence CCen_US
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