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Tag: research

Concerns of Complexity as a Competitive Factor in CHI Conference

CHI research has become more complex (but not more insightful). The reason? Complexity is a competitive factor: it helps separate your paper from others. Lengthy papers with more substudies and details are more likely to do better than short but insightful work that might have more relevance for HCI theory and/or practice. Reviewers are instructed to pay attention to HCI…

The illusion of similarity (in academic research papers)

The illusion of similarity: two papers (A and B) look the same.They have the same structure.They have the same number of words.Both use fluent, nearly flawless English.Both reference the same number of papers.They have the same number of tables and figures. For a layperson, both these papers look the same. Yet, one of them is the worst horsesh*t you’ve ever…

List of Research Superpowers (Especially for PhD Students)

Observed myself citing various “superpowers” to my PhD students in occasional emails. So, thought of writing these down (the list might get updated). Currently, I can think of nine ten superpowers [updated: Sep 1, 2024] for researchers: Being specific is one #researchsuperpower (but it applies well beyond research). Be bold in your writing. I mean, literally, bold your contributions. Just…

The Definitive List of Quantitative Persona Research (Read These to Get a Foundational Understanding of Data-Driven Persona Research)

Here’s a reading list I recommend to “newcomers” in quantitative persona research (e.g., Master’s students, PhD candidates) (see bolded parts for explanations for why you should read each paper). The list contains ten papers and is organized in themes. Conceptual papers discussing the theory of data-driven personas Jung, S.G., Salminen, J. and Jansen, B. J. (2022) Developing Persona Analytics Towards…

Algorithms that describe a researcher’s mind

Algorithms that describe a researcher’s mind: (a) Work on the paper “closest to publication”. => downside: can reduce the willingness to solve difficult problems because they are farther from publication (b) Always switch to more interesting topic, when you see one. => downside: you’ll never get anything published (but upside can be that you learn a lot about different topics,…

Tips on Data Imputation From Machine Learning Experts

Missing values are a critical issue in statistics and machine learning (which is “advanced statistics”). Data imputation deals with ways to fill those missing values. Andriy Burkov made this statement a few days ago [1]: “The best way to fill a missing value of an attribute is to build a classifier (if the attribute is binary) or a regressor (if…

Social media marketing for researchers: How to promote your publications and reach the right people

Today the Social Computing group at Qatar Computing Research Institute had the pleasure of listening to the presentation of Luis Fernandez Luque about social media marketing for researchers. Luis talked about how to promote your publications and personal brand, as well as how to reach the right people on social media with your research. Luis is one of the most…

Startups! Are you using a ‘mean’ or an ‘outlier’ as a reference point?

Introduction This post is about startup thinking. In my dissertation about startup dilemmas [1], I argued that startups can exhibit what I call as ‘reference point bias’. My evidence was emerging from the failure narratives of startup founders, where they reported having experienced this condition. The reference point bias is a false analogy where the founder compares their startup with…