AAAI ICWSM Paper Checklist

Please do not modify the questions and only use the provided macros for your answers. In your paper, please delete all text in the Overview and Detailed Instructions sections, as well as all subsection headers, keeping only the Checklist section heading above along with the questions/answers below.

For each question, change the default Answer to Yes, and, No, because, or NA, when the question seems inappropriate for your research study. You are strongly encouraged to include a justification to your answer, either by referencing the appropriate section of your paper or providing a brief inline description. Within the Checklist section too, you may supplement your answers with a brief discussion that expands on answers to the checklist where necessary. For example:

• •

  Did you include the license to the code and datasets? Yes, see the Methods and the Appendix.

• •

  Did you include the license to the code and datasets? No, because the code and the data are proprietary.

• •

  Did you include the license to the code and datasets? NA

1. 1.

   For most authors…

   1. (a)

      Would answering this research question advance science without violating social contracts, such as violating privacy norms, perpetuating unfair profiling, exacerbating the socio-economic divide, or implying disrespect to societies or cultures? Answer

   2. (b)

      Do your main claims in the abstract and introduction accurately reflect the paper’s contributions and scope? Answer

   3. (c)

      Do you clarify how the proposed methodological approach is appropriate for the claims made? Answer

   4. (d)

      Do you clarify what are possible artifacts in the data used, given population-specific distributions? Answer

   5. (e)

      Did you describe the limitations of your work? Answer

   6. (f)

      Did you discuss any potential negative societal impacts of your work? Answer

   7. (g)

      Did you discuss any potential misuse of your work? Answer

   8. (h)

      Did you describe steps taken to prevent or mitigate potential negative outcomes of the research, such as data and model documentation, data anonymization, responsible release, access control, and the reproducibility of findings? Answer

   9. (i)

      Have you read the ethics review guidelines and ensured that your paper conforms to them? Answer

2. 2.

   Additionally, if your study involves hypotheses testing…

   1. (a)

      Did you clearly state the assumptions underlying all theoretical results? Answer

   2. (b)

      Have you provided justifications for all theoretical results? Answer

   3. (c)

      Did you discuss competing hypotheses or theories that might challenge or complement your theoretical results? Answer

   4. (d)

      Have you considered alternative mechanisms or explanations that might account for the same outcomes observed in your study? Answer

   5. (e)

      Did you address potential biases or limitations in your theoretical framework? Answer

   6. (f)

      Have you related your theoretical results to the existing literature in social science? Answer

   7. (g)

      Did you discuss the implications of your theoretical results for policy, practice, or further research in the social science domain? Answer

3. 3.

   Additionally, if you are including theoretical proofs…

   1. (a)

      Did you state the full set of assumptions of all theoretical results? Answer

   2. (b)

      Did you include complete proofs of all theoretical results? Answer

4. 4.

   Additionally, if you ran machine learning experiments…

   1. (a)

      Did you include the code, data, and instructions needed to reproduce the main experimental results (either in the supplemental material or as a URL)? Answer

   2. (b)

      Did you specify all the training details (e.g., data splits, hyperparameters, how they were chosen)? Answer

   3. (c)

      Did you report error bars (e.g., with respect to the random seed after running experiments multiple times)? Answer

   4. (d)

      Did you include the total amount of compute and the type of resources used (e.g., type of GPUs, internal cluster, or cloud provider)? Answer

   5. (e)

      Do you justify how the proposed evaluation is sufficient and appropriate to the claims made? Answer

   6. (f)

      Do you discuss what is “the cost“ of misclassification and fault (in)tolerance? Answer

5. 5.

   Additionally, if you are using existing assets (e.g., code, data, models) or curating/releasing new assets…

   1. (a)

      If your work uses existing assets, did you cite the creators? Answer

   2. (b)

      Did you mention the license of the assets? Answer

   3. (c)

      Did you include any new assets in the supplemental material or as a URL? Answer

   4. (d)

      Did you discuss whether and how consent was obtained from people whose data you’re using/curating? Answer

   5. (e)

      Did you discuss whether the data you are using/curating contains personally identifiable information or offensive content? Answer

   6. (f)

      If you are curating or releasing new datasets, did you discuss how you intend to make your datasets FAIR (see fair)? Answer

   7. (g)

      If you are curating or releasing new datasets, did you create a Datasheet for the Dataset (see gebru2021datasheets)? Answer

6. 6.

   Additionally, if you used crowdsourcing or conducted research with human subjects…

   1. (a)

      Did you include the full text of instructions given to participants and screenshots? Answer

   2. (b)

      Did you describe any potential participant risks, with mentions of Institutional Review Board (IRB) approvals? Answer

   3. (c)

      Did you include the estimated hourly wage paid to participants and the total amount spent on participant compensation? Answer

   4. (d)

      Did you discuss how data is stored, shared, and deidentified? Answer