Workplan and coaching

Workplan and Coaching

You’ll start working on your project in the second course week. The activities below help you to structure your project. Stick to the plan to ensure you can finish the project in time.

Deliverables are submitted on Canvas and due by Friday, 7 pm, of the respective course week. The course team will provide short feedback in writing at least a day before the next coaching session.

Week 1: Team Formation

  • Explore whom you would like to work with.
  • Register your team on Canvas.

Week 2: Idea Generation (Coaching #1)

  • Coaching Support:
    • Discuss your research question, business problem, or knowledge gap with your coach (and use Table 2 in Boegershausen et al. 2022 for refinement).
    • Identify potential data sources (preferably in a list).
    • Assess the feasibility of the project: Is it realistic and achievable within the course timeframe? Is the research question or context engaging?
    • Address any installation issues.
  • Progress on Source Code:
    • Connect to the data sources you’ve considered (e.g., web scraping, APIs) to determine their accessibility.
  • Deliverables:
    • Section 1: Questions 1.1-1.2 of your data documentation.

Diversity & inclusion matters!

While we try to start the conversation about potential topics to work on around specific themes, we ask you not to feel restricted by those. In fact, what really matters here is that you bring in your passion (e.g., hobby), background (e.g., nationality, ethnicity), or any other thing that you consider part of yourself. In other words, let’s bring alive Tilburg’s statement of diversity and inclusion. If you’re really into scraping Amazon.com, that’s fine. But if you’re more interested in that niche platform that you and some of your friends hang out on, feel welcome to do that! We’re not just here to do what others have done in the past, but we’re here to move our field along. And we won’t be able to do that without talking about and doing the things that you truely care about.

Please also check out the syllabus for some more information on how diversity & inclusion matters in this class.

Week 3: Data Source Selection (Coaching #2)

  • Coaching Support:
    • Review your initial data source or research question with your coach; adjust if impractical (and use Table 2 in Boegershausen et al. 2022 for refinement).
    • Ensure all team members contribute, including coding.
    • Address any questions related to Section 1 of your draft data documentation.
  • Progress on Source Code:
    • Gain access to the data source and choose a method for data retrieval (e.g., BeautifulSoup, Selenium, or API).
    • Ensure team members can access the data source, and encourage code sharing within the team.
  • Deliverables:
    • Section 1: Complete all questions of your data documentation.

Week 4: Extraction Design (Coaching #3)

  • Coaching Support:
    • Design your data extraction plan: Decide what to retrieve, which seeds to use, frequency, and processing methods. Use Table 3 in Boegershausen et al. 2022 throughout.
    • Resolve any questions related to Sections 1-2 of your draft data documentation.
  • Progress on Source Code:
  • Deliverables:
    • Sections 1-2 of your data documentation.
    • Prepare a presentation for Week 5.

Please adhere to the following presentation structure

  • Title page: Team number & brief description of (updated) motivation for data context
  • Slide 1: Which information to extract from which pages/endpoints? (Challenge #2.1)
  • Slide 2: Which seeds to use as a starting point of the data collection? (Challenge #2.2)
  • Slide 3: At which frequency to extract information (Challenge #2.3)
    • please include a calculation of your study’s feasible sample size.
  • Slide 4: How to process the information during the extraction? (Challenge #2.4)

Throughout, provide details on how your extraction design balances technical feasibility and exposure to potential legal and ethical risks (cf. Table 3 in “Fields of Gold”).

Please upload the presentation (as a PDF) and Excel sheet (as an Excel file) with the sample size calculations in one zip file, at the latest a day before the presentation sessions (see schedule).

Week 5: Prototype Development (Coaching #4)

  • Coaching Support:
    • Finalize a functional prototype.
    • Seek feedback and resolve technical issues.
    • Implement monitoring tools and decide on infrastructure. Use Table 4 in Boegershausen et al. 2022 throughout.
    • Discuss preprocessing and potential use cases.
  • Progress on Source Code:
    • Implement monitoring tools and infrastructure.
    • Further refine data extraction; consider completing advanced tutorials.
  • Deliverables:
    • Sections 1-3 of your data documentation.

Week 6: Technical Refinement (Coaching #5, optional)

  • Coaching Support:
    • Continue refining data collection.
    • Inspect data, gather feedback on potential plots (section 5), and start discussing initial plots and summary statistics.
  • Progress on Source Code:
    • Resolve technical difficulties and focus on completing data extraction.
    • Continue progressing towards final documentation.

Week 7: Final Technical Refinement (Coaching #6, optional)

  • Coaching Support:
    • Get feedback on any remaining technical issues.
    • Aim to complete all remaining tasks.
  • Progress on Source Code:
    • Final debugging and data extraction completion.