Three ways of justifying/arguing for research choices (e.g., hyperparameter values, thresholds, sample sizes):
This post deals with understanding various types of contributions in academic research (SECTION 1) and how to argue for your contribution (SECTION 2). This post is written especially for more junior researchers, including PhD students. SECTION 3 contains alternative contribution frameworks from other researchers. SECTION 1: Some forms of contributions in academic research: Should you aim for multiple contribution types…
Here’s a reading list I recommend to “newcomers” in quantitative persona research (e.g., Master’s or PhD students). See bolded parts for explanations for why you should read a given paper. NOTE: There are *many more* important data-driven persona papers. Why I only included papers from our team in this list is because this blog post is a part of a…
Here are som algorithms that describe researchers’ mind, especially how they choose and pursue research topics: (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…
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…
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…
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…
Introduction I ran an analysis with IBM Watson Personality Insights. It retrieved my tweets and analyzed their text content to describe me as a person. Doing so is easy – try it here: https://personality-insights-livedemo.mybluemix.net/ I’ll briefly discuss the accuracy of the findings in this post. TL;DR: The accuracy of IBM Watson is a split decision – some classifications seem to…
Just a picture of a black sheep. Introduction. Hal Daumé III wrote an interesting blog post about language bias and the black sheep problem. In the post, he defines the problem as follows: The “black sheep problem” is that if you were to try to guess what color most sheep were by looking and language data, it would be very…
Introduction The ambiguity problem illustrated: User: “Siri, call me an ambulance!” Siri: “Okay, I will call you ‘an ambulance’.” You’ll never reach the hospital, and end up bleeding to death. Solutions Two potential solutions: A. machine builds general knowledge (“common sense”) B. machine identifies ambiguity & asks for clarification from humans The whole “common sense” problem can be solved by…
