6 Matching Annotations
- Feb 2020
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journals.sagepub.com journals.sagepub.com
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Social media research ethics faces a contradiction between big data positivism and research ethics fundamentalism. Big data positivists tend to say, ‘Most social media data is public data. It is like data in a newspaper. I can therefore gather big data without limits. Those talking about privacy want to limit the progress of social science’. This position disregards any engagement with ethics and has a bias towards quantification. The ethical framework Social Media Research: A Guide to Ethics (Townsend and Wallace, 2016) that emerged from an ESRC-funded project tries to avoid both extremes and to take a critical-realist position: It recommends that social scientists neither ignore nor fetishize research ethics when studying digital media.Research ethics fundamentalists in contrast tend to say,You have to get informed consent for every piece of social media data you gather because we cannot assume automatic consent, users tend not to read platform’s privacy policies, they may assume some of their data is private and they may not agree to their data being used in research. Even if you anonymize the users you quote, many can still be identified in the networked online environment.
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One important aspect of critical social media research is the study of not just ideolo-gies of the Internet but also ideologies on the Internet. Critical discourse analysis and ideology critique as research method have only been applied in a limited manner to social media data. Majid KhosraviNik (2013) argues in this context that ‘critical dis-course analysis appears to have shied away from new media research in the bulk of its research’ (p. 292). Critical social media discourse analysis is a critical digital method for the study of how ideologies are expressed on social media in light of society’s power structures and contradictions that form the texts’ contexts.
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Besides conducting qualitative social research with social media users in order to learn about their experiences, interpretations and perspectives, critical digital methods should not completely discard tools for digital data collection and analytics but take their use into a new direction. Critical digital methods should certainly engage in collecting and analys-ing samples of data from social media platforms with the help of tools and services, such as DiscoverText, Tweet Archivist, Netvizz, NodeXL, Gephi, NCapture/NVivo, Sodato, Import.io, InfoExtractor, Google Web Scraper, TAGS, SocioViz and so on.
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t has, for example, been common to study contemporary revolutions and protests (such as the 2011 Arab Spring) by collecting large amounts of tweets and analysing them. Such analyses can, however, tell us nothing about the degree to which activists use social and other media in protest communication, what their motivations are to use or not use social media, what their experiences have been, what problems they encounter in such uses and so on. If we only analyse big data, then the one-sided conclusion that con-temporary rebellions are Facebook and Twitter revolutions is often the logical conse-quence (see Aouragh, 2016; Gerbaudo, 2012). Digital methods do not outdate but require traditional methods in order to avoid the pitfall of digital positivism. Traditional socio-logical methods, such as semi-structured interviews, participant observation, surveys, content and critical discourse analysis, focus groups, experiments, creative methods, par-ticipatory action research, statistical analysis of secondary data and so on, have not lost importance. We do not just have to understand what people do on the Internet but also why they do it, what the broader implications are, and how power structures frame and shape online activities
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Studying digital and social media could take inspiration by the tradition going back to Karl Marx and other critical theorists
A need to think about the context and broader social implications of the research being conducted.
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There is a tendency in Internet Studies to engage with theory only on the micro- and middle-range levels that theorize single online phenomena but neglect the larger picture of society as a totality (Rice and Fuller, 2013). Such theories tend to be atomized. They just focus on single phenomena and miss soci-ety’s big picture
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