[Air-L] Call for Submissions: DATASET CHALLENGE at the 2nd European Symposium on Societal Challenges in Computational Social Science

Weller, Katrin Katrin.Weller at gesis.org
Mon Jun 11 04:24:14 PDT 2018


2nd European Symposium on Societal Challenges in Computational Social Science:
BIAS AND DISCRIMINATION

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DATASET CHALLENGE - CALL FOR CONTRIBUTIONS
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Euro CSS Symposium
#eurocss
December 5-7, 2018
Cologne, Germany
Website: http://symposium.computationalsocialscience.eu
Easychair: https://easychair.org/conferences/?conf=csssymposium18
For inquiries: css.eurosymposium at gmail.com<mailto:css.eurosymposium at gmail.com>


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IMPORTANT DATES
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* Deadline for abstract submissions to the dataset challenge: September 1, 2018
* Deadline for travel grant applications: September 1, 2018
* Notification of acceptance: September 15, 2018
* Pre-conference day (incl. dataset challenge presentations): December 5, 2018
* Main Symposium: December 6-7, 2018

Please watch out for our additional calls for
* main symposium contributions (talks/posters)
* workshop and tutorials
* phd consortium (forthcoming)

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ABOUT THE DATASET CHALLENGE
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For the first Dataset Challenge as part of our European Symposium on Societal Challenges in CSS, we invite researchers and practitioners from the spectrum of Social and Computational Sciences to approach a common dataset. The aim of this challenge is to encourage creative engagement with data from pluralistic perspectives in order to foster dialogue across disciplines. We envision that this challenge will lead to fruitful, in-depth discussions during the symposium, as participants will have a shared basis through interaction with the dataset(s), but varying ideas of where to go with it.

The research questions and methods applied to the dataset(s) can be drawn from the broad spectrum of Computational Social Science. They should ideally be related to this year's symposium topic 'bias and discrimination' and approach new ways of learning about bias, be it by putting forward new research designs and questions, or by applying state-of-the-art methods to identify data patterns that can inform theory building. Topics of interest include but are not limited to:

* Comparisons of user/political actor behaviour
* Unequal structures and political action
* Biases in Web data
* Missing data
* Coverage bias on different platforms / through different collection methods

We ask participants of the dataset challenge to be creative in their approach to the data.

The work presented at the symposium can be early stage, but should be methodically sound and provide either preliminary insights into an interesting research question or first inductively-reached conclusions of systematic patterns of bias in the dataset. These can also be on a meta-level or may be designated to positioning the work in broader theoretical contexts, e.g., about biases in the data collection. We especially invite inventive combinations with other datasets (e.g., digital trace data, survey data, multimedia data, multilingual data, data from other case studies).

Submissions selected by our review committee will be presented in a special dataset challenge session at the pre-symposium day (December 5, 2018).

A jury will select the best presentation (including any created resources, such as secondary datasets or analysis code) to be awarded the very first Euro CSS Dataset Challenge Award.

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SUBMISSION GUIDELINES
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Extended abstracts of work in progress or completed projects based on the suggested dataset(s) should be submitted in English in PDF format via the EasyChair submission system: https://easychair.org/conferences/?conf=csssymposium18

Submissions should be abstracts of approx. 2-3 pages (maximum up to 1000 words plus references and figures).

The abstract submissions will be evaluated based on originality and the potential to stimulate interesting discussions, but should also consider the feasibility of the proposed idea. Please consider that reviewers will be from an interdisciplinary community, therefore describe your ideas, approaches and potential complementary datasets in sufficient detail.

Deadline for submissions to the dataset challenge is September 1, 2018. The final work will be presented at the symposium.

Please see the website for additional information on how to apply for travel grants.

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THE DATASETS
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The provided datasets all relate to the topic of political communication in Germany, particularly around the German federal election which took place in September 2017. Participants of the challenge should make use of one or more of the main datasets listed below and are encouraged to combine them or compare them among each other.

Additional datasets listed on the website may also be used, as well as any other datasets of the participants' choice (qualitative, quantitative, textual, multimedia, etc.).

Main Datasets (participants must choose at least one of these):

[1] Algorithmwatch's user-donated search results dataset for the German Federal Elections 2017. Personalized search results when looking up political topics.

[2] Abgeordnetenwatch.de - All members of the German parliaments and their votes, description of vote contents and much more metadata.

[3] Social media content generated by candidates during the German federal election 2017 and resonance with their follower-base.

Please see our website for detailed information about the datasets: http://symposium.computationalsocialscience.eu/2018/#data.

It also lists further auxiliary Datasets.


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FAQ / ASSISTANCE
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For any questions related to technical aspects, data structure and especially German language that might come up with these datasets, please do not hesitate to contact us!

Please feel free to use our Google Group / mailing list 'CSSnet' for discussions about the dataset challenge, for looking for potential collaborations, or to ask questions to the community: https://groups.google.com/forum/#!forum/cssnet

Specific questions can also be sent to us directly at css.eurosymposium at gmail.com<mailto:css.eurosymposium at gmail.com>.


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Dr. Katrin Weller
GESIS Leibniz Institute for the Social Sciences
Dept. Computational Social Science
Unter Sachsenhausen 6-8
D-50667 Köln
Germany

E-Mail: katrin.weller at gesis.org<mailto:katrin.weller at gesis.org>
Twitter: @kwelle
Web: http://katrinweller.net<http://katrinweller.net/>




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