***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