Digital technologies continue to reshape and reimagine core research practices, from transcribing interviews, to creating entire texts autonomously. This list brings together some of the top posts on research technologies that have featured on the LSE Impact Blog in 2019.
The transcription of verbal and non-verbal social interactions is a central feature of social research and remains one of the most labour intensive and time consuming parts of many research projects. In this post Daniela Duca explores how the automation of transcription has become standard practice in other industries, such as news media, and considers what this might mean for approaches to analysing and interpreting qualitative data.
Being able to find, assess and place new research within a field of knowledge, is integral to any research project. For social scientists this process is increasingly likely to take place on Google Scholar, closely followed by traditional scholarly databases. In this post, Alberto Martín-Martín, Enrique Orduna-Malea , Mike Thelwall, Emilio Delgado-López-Cózar, analyse the relative coverage of the three main research databases, Google Scholar, Web of Science and Scopus, finding significant divergences in the social sciences and humanities and suggest that researchers face a trade-off when using different databases: between more comprehensive, but disorderly systems and orderly, but limited systems.
As research into AI has become more developed, so too has the understanding that AI research might be misused. Discussing OpenAI’s recent decision to withhold the source code for an algorithm designed to replicate handwriting, citing concerns for the public good, Gabrielle Samuel argues that blanket commitments to openness are insufficient to protect against the potential ‘dual-use’ of AI research and that AI researchers need to develop a shared ethical code of conduct for releasing their research findings.
Twitter and other social media platforms represent a large and largely untapped resource for social data and evidence. In this post, Wasim Ahmed updates his recurring series on the Impact Blog, to bring you the latest developments in digital methods and methodologies for researching Twitter and other social media platforms.
When social scientists think about big data, they often think in terms of quantitative number crunching. However, the growing availability of ‘big’ qualitative datasets presents new opportunities for qualitative research. In this post, Lynn Jamieson and Sarah Lewthwaite explore how ‘big qual’ can be deployed as a distinct research methodology to develop new forms of qualitative research and elucidate complex interactions between largescale qualitative datasets.
Artificial Intelligence (AI) has been applied to an increasing number of creative tasks from the composition of music, to painting and more recently the creation of academic texts. Reflecting on this development Harry Collins, considers how we might understand AI in the context of academic writing and warns that we should not confuse the work of algorithms with tacit complex socially constructed forms of knowledge.
In this post Dr Reka Solymosi & Dr Michael Chataway discuss the use of mobile phone applications as a research method in the social sciences. Reflecting on their own use of apps to study fear of crime, they highlight the methodological advantages of incorporating apps into research designs and provide four key points to consider for researchers seeking to use apps in their projects.
Andreas Pacher presents the Observatory of International Research (OOIR), a research tool that provides users with easy to use overviews and information for whole fields of social science research. Reflecting on the advantages and limitations of other discovery tools and the potential for information overload, Andreas points to the utility of OOIR in producing search results that are both broad based and tailored to specific academic interests.
Paper Digest is a new research tool that uses artificial intelligence to produce summaries of research papers. In this post David Beer tests out this tool on his own research and reflects on what the increasing penetration of AI into cognition and research tells us about the current state of academic research.
In this post Shalini Kurapati introduces the concept of data stewarding. Drawing on her own experience, she describes how data stewarding has developed an important role in delivering open science and research in higher education and research institutions and discusses how data stewarding also presents an important opportunity for post-doctoral researchers to develop careers within and beyond academia.
The revolutionary potential of blockchain has been much touted in many fields including research and higher education. In this post, Martin Hamilton discusses some of the potential applications of blockchain to academia and raises key questions about how these systems could be implemented and safeguarded from malicious exploitation.
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