Category: Data science

Why the ban on P-Values? Understanding sampling error is key to improving the quality of research.

The weight placed on p-values and significance testing has come under increasing criticism, with one social psychology journal banning their use entirely. Nicole Radziwill argues that many of the issues come down to sampling errors. Inferential statistics is good because it lets us make decisions about a whole population based on one sample. But inferential statistics is bad if your sample size is too […]

The researcher’s guide to literature: Visualising crowd-sourced overviews of knowledge domains.

Given the enormous amount of new knowledge produced every day, keeping up-to-date on all the literature is increasingly difficult. Peter Kraker argues that visualizations could serve as universal guides to knowledge domains. He and colleagues have come up with an interactive way of automating the visualisations of entire knowledge domains and relevant articles within fields. Through similarity measures identified in a Mendeley powered data-set, an interested […]

Philosophy of Data Science – Emma Uprichard: Most big data is social data – the analytics need serious interrogation

In the final interview in our Philosophy of Data Science series, Emma Uprichard, in conversation with Mark Carrigan, emphasises that big data has serious repercussions to the kinds of social futures we are shaping and those that are supporting big data developments need to be held accountable. This means we should also take stock of the methodological harm present in many big data […]

Introduction to Open Science: Why data versioning and data care practices are key for science and social science.

A significant shift in how researchers approach their data is needed if transparent and reproducible research practices are to be broadly advanced. Carly Strasser has put together a useful guide to embracing open science, pitched largely at graduate students. But the tips shared will be of interest far beyond the completion of a PhD. If time is spent up front thinking about file organization, sample […]

Philosophy of Data Science series – Sabina Leonelli: “What constitutes trustworthy data changes across time and space”

The next installment of the Philosophy of Data Science series is with Sabina Leonelli, Principal Investigator of the ERC project, The Epistemology of Data-Intensive Science. Last year she completed a monograph titled “Life in the Digital Age: A Philosophical Study of Data-Centric Biology”, currently under review with University of Chicago Press. Here she discusses with Mark Carrigan the history of data-centric science and […]

A political economy of Twitter data? Conducting research with proprietary data is neither easy nor free.

Social media research is on the rise but researchers are increasingly at the mercy of the changing limits and access policies of social media platforms. API and third party access to platforms can be unreliable and costly. Sam Kinsley outlines the limitations and stumbling blocks when researchers gather social media data. Should researchers be using data sources (however potentially interesting/valuable) […]

Qualitative and quantitative research are fundamentally distinct and differences are paramount to the social sciences

Matt Vidal calls for clear distinctions to be made between qualitative and quantitative research. Using as an example the impartial data generated by surveys, Vidal argues that such quantitative data are fundamentally important, but incomplete. Data based on methods of prolonged engagement with respondents are qualitative, also important, but incomplete. Both are united in their goal of advancing knowledge and theory, […]

Philosophy of Data Science series – Noortje Marres: Technology and culture are becoming more and more entangled.

Mark Carrigan continues his investigation of data science with this latest interview with Noortje Marres on Digital Sociology. Growing digital awareness means lots of opportunities for collaboration between sociology and related fields and there is also a chance for sociologists to challenge the deeply-rooted narrative of a clash between technology and democracy. This interview is part of an ongoing series on the Philosophy of […]

Stand Up and Be Counted: Why social science should stop using the qualitative/quantitative dichotomy

Qualitative and quantitative research methods have long been asserted as distinctly separate, but to what end? Howard Aldrich argues the simple dichotomy fails to account for the breadth of collection and analysis techniques currently in use. But institutional norms and practices keep alive the implicit message that non-statistical approaches are somehow less rigorous than statistical ones. Over the past year, I’ve met with many doctoral students […]

Five Minutes with Marieke Guy: “By opening up data, citizens can be more directly informed and involved in decision-making.”

What exactly is open data and how does it relate to education? Marieke Guy from the Open Knowledge Foundation will be speaking at the LSE this Wednesday 26 November 5-7pm as part of the Learning Technology and Innovation NetworkED series (booking still open). Ahead of her talk she answers a few questions on the opportunities and vulnerabilities involved in providing greater access to […]