***Apologies for cross-posting
Dear colleagues,
I am delighted to draw your attention to the special issue "Exploring the methodological choices, challenges and solutions in working with new data sources" in the journal methods data analyses (mda). Guest editors are Trent D. Buskirk (Bowling Green State University) and Rachel Gibson (University of Manchester).
Link to mda call for papers (see also below): https://mda.gesis.org/index.php/mda/announcement/view/7
Best regards Jan
*CALL FOR PAPERS* 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 ‘norm’, 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.
This special issue will explicitly address these challenges and thus help to build the growing trend towards an ‘open research’ 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.
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.
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.
- Empirical research that employs mixed methods of data collection e.g. mixed-mode designs that link new data with traditional survey approaches. - Papers that use new data collection or access techniques such as purpose-built apps suitable for mobile devices or using social media platforms for recruitment. - Papers that access and analyze new forms of data on sensitive topics. - Papers that combine new data sources with survey data to compare quality or improve overall understanding of outcomes of interest. - Research that uses new types of data to enhance survey research designs or analyses. - Research that explores the use of multiple new data types for generating estimates of outcomes of interest
Ultimately, we envisage a collection of papers that form a ‘must read’ for those seeking to conduct a project that uses any type of social media or digital trace data. The reflective statement is designed to encourage authors to openly discuss the problems and critical decisions they faced when working with and generating meaningful findings from new forms of ‘big’ data. The volume itself, and the approach of ‘reflexive praxis’ that it promotes we envisage as offering a new approach to knowledge production and sharing and a significant advance toward embedding the values of open research within the scientific community.
*Submission procedure and timeline* If you are interested in submitting an article to the mda special issue on “ Exploring the Methodological Choices, Challenges and Solutions in working with New Data Sources ”, please send an extended abstract documenting the main research questions, design of the study, and proposed analyses (500 - 1000 words) to before May19, 2023. The abstracts will be evaluated by the guest editors. For the selected abstracts, authors will be invited to contribute full papers that will be subjected to peer-review. Authors of all accepted manuscripts will be required to submit a reflective methodological statement (maximum 500-750 words) that will be reviewed by the editors and published online as an appendix. Guidelines for manuscript preparation and the appendix material can be found in the information for authors: http://mda.gesis.org/index.php/mda/about/submissions#authorGuidelines. Papers should be submitted online via Open Journal Systems (https://mda.gesis.org/index.php/mda). Full papers are due by October 2, 2023. Accepted papers will be published Online First. The special issue will appear in early fall, 2024.
- The detailed time schedule is as follows: - Call for Papers: March 2023 - Deadline for the submission of extended abstracts (500–1,000 words): May 19th 2023 - Decision on the abstracts: w/c June 19th 2023 - Deadline for submission of the full papers: October 2nd, 2023 - Decision on the full papers: December 31st, 2023 - Deadline for the submission of revised manuscripts: March 2024 - Final decision: April 2024 - Layout/Online first publication: May-August 2024 - Publication of the Special Issue: September 2024