{"id":2343,"date":"2023-03-27T16:43:30","date_gmt":"2023-03-27T15:43:30","guid":{"rendered":"https:\/\/sites.manchester.ac.uk\/diced\/?p=2343"},"modified":"2023-03-27T17:30:36","modified_gmt":"2023-03-27T16:30:36","slug":"%f0%9f%93%a2cfp-for-special-issue-of-mda-about-methodological-choices-challenges-and-solutions-with-new-data-sources","status":"publish","type":"post","link":"https:\/\/sites.manchester.ac.uk\/diced\/2023\/03\/27\/%f0%9f%93%a2cfp-for-special-issue-of-mda-about-methodological-choices-challenges-and-solutions-with-new-data-sources\/","title":{"rendered":"?CFP for Special Issue of mda about Methodological Choices, Challenges and Solutions with New Data Sources"},"content":{"rendered":"

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Exciting news to start this week: The Call for Papers for a Special Issue of mda<\/strong><\/a> (methods, data, analyses), a journal published by GESIS, is officially out! This special issue, which is called “Exploring the Methodological Choices, Challenges and Solutions in working with New Data Sources”, is co-edited by Trent Buskirk and our own Rachel Gibson.<\/p>\n

Read on below for more information on how to submit your abstract(s).<\/p>\n

Call for Papers for Special Issue of mda:<\/strong><\/h3>\n

Exploring the Methodological Choices, Challenges and Solutions in working with New Data Sources<\/strong><\/h4>\n

With new data come new opportunities and challenges. In this Special Issue of methods, data, analyses (mda) we will explore and promote scholarly reflection and transparency on emerging best practices in the collection, processing, analysis and sharing of new data sources within the research community. This topic is of growing importance to quantitative and computational social science researchers given that social media and digital trace data, as well as data collected from sensors, are now widely used in many areas of inquiry. Currently there is a growing body of research that documents the exploration, evaluation and use of these new data types with some researchers noting how social media and digital trace data, for example, have properties that deviate from the \u2018norm\u2019, both in regard to their basic format, underlying (lack of) structure, and representativeness. However, the current state of the research offers little in the way of emerging best practices. In particular, how are social scientists leveraging their methodological skills and techniques to overcome some of the inherent challenges being faced when working with these new data sources? Even more fundamental are the challenges researchers face after data collection and analysis begins. Given both the merits and these known and unknown problems in the collection and analysis of many types of new and emerging data sources there is now an increasing need for researchers to openly confront and interrogate the assumptions and processes followed in working with them.<\/p>\n

This special issue will explicitly address these challenges and thus help to build the growing trend towards an \u2018open research\u2019 culture by making the decision-making around working with emerging data sources, such as social media and digital trace data, more transparent. Specifically, we seek to publish papers that use new forms of data, methods and analyses but that also include an appendix in which the authors provide a peer edited, public commentary on the process followed to achieve their end results. The goal will be to both publish high quality research but also to show how research practices were adjusted and revised to accommodate challenges and unexpected problems presented in working to access, process and analyze these new types of data over the course of the research process. The peer edited appendices will help readers better understand the methodological pathway and course of decision-making involved in implementing a research design that is reliant on one or many new or emerging data sources. We think of these peer edited reflections as a lens into steps researchers needed to take between methods they originally planned to deploy and those they ended up using in their final approach in part due to unforeseen issues or obstacles when dealing with new data sources and access platforms.<\/p>\n

We welcome papers on range of topics that address new or existing substantive social science questions or debates using new forms of data, particularly data generated as digital traces or via social media platforms. Given the interests of mda, we especially invite authors to submit articles extending the profession’s knowledge on the opportunities and problems involved in linking social media, digital trace or sensor data, for example, to other types of data such as that generated through surveys, as well as administrative data, such as census or electoral roll information. While we impose no restrictions on topics investigated or the methods used for collecting and analyzing the data, a key requirement is that authors generate and append a reflective statement to their paper setting out the choices, challenges they encountered when working with these emergent data sources as well as a discussion of the solutions they deployed to move the analysis and study forward. More details of what is required can be found in the template for supplementary peer review material attached to this call for papers.<\/p>\n

Some examples of types of papers likely generate high impact reflective statements, i.e. that would form a valuable practical guide for other researchers in the field, are detailed below.<\/p>\n