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Subject: data protection ×

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    Information Provision for Informed Consent Procedures in Psychological Research Under the General Data Protection Regulation: A Practical Guide
    (Thousand Oaks, CA : Sage Publishing, 2023) Hallinan, Dara; Boehm, Franziska; Külpmann, Annika Iris; Elson, Malte
    Psychological research often involves the collection and processing of personal data from human research participants. The European General Data Protection Regulation (GDPR) applies, as a rule, to psychological research conducted on personal data in the European Economic Area (EEA)—and even, in certain cases, to psychological research conducted on personal data outside the EEA. The GDPR elaborates requirements concerning the forms of information that should be communicated to research participants whenever personal data are collected directly from them. There is a general norm that informed consent should be obtained before psychological research involving the collection of personal data directly from research participants is conducted. The information required to be provided under the GDPR is normally communicated in the context of an informed consent procedure. There is reason to believe, however, that the information required by the GDPR may not always be provided. Our aim in this tutorial is thus to provide general practical guidance to psychological researchers allowing them to understand the forms of information that must be provided to research participants under the GDPR in informed consent procedures.
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    About Migration Flows and Sentiment Analysis on Twitter Data: Building the Bridge Between Technical and Legal approaches to data protection
    (Paris : European Language Resources Association (ELRA), 2022) Gottschalk, Thilo; Pichierri, Francesca; Rigault, Mickaël; Arranz, Victoria; Siegert, Ingo
    Sentiment analysis has always been an important driver of political decisions and campaigns across all fields. Novel technologies allow automatizing analysis of sentiments on a big scale and hence provide allegedly more accurate outcomes. With user numbers in the billions and their increasingly important role in societal discussions, social media platforms become a glaring data source for these types of analysis. Due to its public availability, the relative ease of access and the sheer amount of available data, the Twitter API has become a particularly important source to researchers and data analysts alike. Despite the evident value of these data sources, the analysis of such data comes with legal, ethical and societal risks that should be taken into consideration when analysing data from Twitter. This paper describes these risks along the technical processing pipeline and proposes related mitigation measures.