Participants may work individually or in teams.
Participants must define what they mean by disinformation.
Participants must use data related to at least two social media. Data from just on-line mainstream news sites is only of tertiary interest.
Participants must address one of the three questions above.
Participants should address a social science theory or policy relevant issue and should employ one or more methodologies appropriate for the empirical assessment of or forecasting on the basis of big data (e.g., computational algorithms, machine learning, computer simulation, social network analysis, text mining).
Each participating team may prepare one or more entry.
Entries must represent original work that has not been previously published or submitted to other challenges.
Participants are encouraged to use any data set of interest. However, this data must be provided along with the challenge paper. This data will become part of a public repository. To that end – a) the names of individuals in the data set (or their social media id), must be de-identified, b) the ids of specific social media posts should be replace by fake ids. If the submitting team does not know how to do that, Dr. Kathleen Carley will have a third party run a de-identifier on the data for the participating team.
At the conference, all entries will be judged by the community using a participant voting system.
Top entries may be invited to submit full length paper describing their challenge solution in a SBP-BRiMS special issue of the journal of Computational and Mathematical Organization Theory.

A strong entry generally has one or more of these components:

Employ multiple data sets.
Be theory based.
Include at least one high quality visualization (note that participants will be allowed to display dynamic visualizations via some form of electronic media e.g., by hanging a tablet from the poster. However, please note that tables will not be provided.
Account for biases in the data across time, space, topics and sources.
Demonstrates a deep understanding of the problem being addressed.
Providea a new metric, simulation or algorithm development such as:

A new spatial, temporal, or network analytic methodology or algorithm, or a simulation model, that can cope with the vast scale of open source data (e.g.Twitter data) and support answering a key social or policy issue.
A new spatial analytic methodology that can better take into account change over time and non-spatial distances (such as co-occurrences and semantic similarity between locations).
A new network methodology that better incorporate the diversity of actor and relationship types in the data, spatio-temporal information, or for constructing edges from the data and for distributing actor and edge attributes onto the graph.
A novel simulation that that supports reasoning about the spread of fake news or propaganda that uses empirical data to either instantiate the model or to confirm some of the results.

Generates a new empirical finding that challenges or provides novel support for existing social or political theory, or provides information of policy relevance. Note, the results of computer simulation are viewed as empirical findings.

In addition, a strong entry should be well-written and provide some level of creativity in its use of or combination of data.

You need to submit 3 things - 1 page paper in conference format, an 8 minute video, and a single powerpoint teaser slide - that we can use to promote your entry. All three of these will go in the non-archival on-line proceedings.

Challenge Paper: A 1-page paper describing the project. This includes references as well. This should define:

Promotion/teaser Slide:
This is a single powerpoint slide. The purpose of this slide is to excite people to come to your poster. This slide will also be put on line. We will use this slide to promote your entry. This slide should contain:

Challenge Response Submission: 22-August-2022. 1 page paper in conference format, an 8 minute video, and a single powerpoint teaser slide.

All entries will send at least one team member to SBP-BRiMS who will be registered for the conference by the early registration deadline to represent their entry. The winning entry will give a short talk on the last day of the conference. This will be a 12 minute talk with 3 minutes for questions.

Anyone with an interest in using this data to address a social or policy issue. Entries are accepted from single individuals or teams.

Suggestion: Participants may want to use Jupyter to demonstrate their code and results. Examples can be found here, Sample Jupyter Notebooks.

The final paper for the winning entry will be published in the journal of Computational and Mathematical Organization Theory – in the SBP-BRiMS special issue.

A member of the team that developed the winning entry will do a short presentation on either Thursday or Friday at the conference describing the response.