Research Programme on AI & Work
This programme supports research in the sphere of AI & Work.
Bernie Hogan (PhD Toronto, 2009) is a Associate Professor, Senior Research Fellow at the OII and Research Associate at the Department of Sociology. With training in sociology and computer science, Hogan focuses on how social networks and social media can be designed to empower people to build stronger relationships and stronger communities.
Hogan’s theoretical work was among the first to identify the role of the social media platform as curator and to distinguish certain social media as the ‘real name web’. His practical work has shown how network visualizations can reveal new information to individuals from their social media data. He believes that the way networked information comes us in feeds is akin to being given a route through social space. This might get us where we want to go, but to truly empower people we need to see the map, not only the route along the way.
Hogan’s innovations in social network analysis began with his work at NetLab at the University of Toronto. With Barry Wellman and fellow graduate students, he introduced participant-aided sociograms as a means to capture social networks with pen and paper. He subsequently applied this to social media, and especially Facebook with the introduction of NameGenWeb, a Facebook network visualizer (with Joshua Melville). The second generation of this visualizer, CollegeConnect, was empirically shown to help high school students reveal social resources in their networks. Most recently, with Melville and collaborators at the Institute for Sexual and Gender Minority Health and Wellbeing at Northwestern University, he has been working on Network Canvas. This software makes the collection of self-reported network data accessible to non-technical researchers.
Hogan has published in a wide variety of venues, from peer-reviewed papers in sociology journals (such as Social Networks, City and Community, Bulletin of Science Technology and Society, and Field Methods), in computer science proceedings (such as CHI, ICWSM, and CSCW) and related disciplines, particularly geography (with papers in Environment and Planning B, the Annals of the Association of American Geographers and Tijdschrift voor Economische en Sociale Geografie) and communication (with papers in New Media & Society, Social Media + Society, International Journal of Communication, and Information, Communication and Society). This is in addition to many chapters in books, grey literature reports and public opinion pieces. He is on the editorial boards of Social Media + Society, Journal of Computer-Mediated Communication and Social Networks.
Public dissemination of research is a core part of Hogan’s work. With colleagues, he has worked with UK therapy organizations, Tavistock and Relate to produce guidelines on internet infidelity for patients and practitioners. He has also published related work in the Journal of Marital and Family Therapy. He has been featured on BBC 1 morning and Newsnight, ITV, Channel 4, Channel 5, Vice and NBC in America. He is routinely featured on BBC 4 radio including as a mentor in Radio 4’s So You Want to Be a Scientist. He has given keynotes at conferences in France, UK, Switzerland and Japan.
As an academic Hogan is keen on service to the University and the wider academic community. He has run small academic seminars on Internet and Relationships at the OII as well as hosting the International Conference on Web and Social Media at Oxford in 2015. He was previously program chair for ICWSM in 2013 and 2014 and is currently a member of the ICWSM steering committee.
Many of Hogan’s papers can be found at his ssrn page and registered on his Google scholar. His ORCID is here. He is currently accepting graduate students on his active interests of names and naming practices, egocentric social networks, network visualizations, politics of social media and social identity, especially identity issues relating to gender and sexual minorities.
This programme supports research in the sphere of AI & Work.
With the introduction of open source AI tools for image generation, communities of practice exist that can generate image models trained on real people. This project explores how such communities develop norms about the appropriate use of a likeness.
The Oxford COVID-19 Project aims to increase our understanding of COVID-19 and elaborate possible strategies to reduce the impact on the society through the combined power of Statistical, Mathematical Modelling and Machine Learning techniques.
27 October 2023
The OII is leading the debate on Artificial Intelligence. Generative AI has been a key area of interest for faculty, researchers and students for many years. This article brings together some of this work to date and highlights forthcoming work.
11 September 2023
The Oxford Internet Institute is deeply saddened to learn of the passing of Dr Amaru Villaneuva Rance in 2022. Amaru was an alumnus of the OII’s MSc Social Science of the Internet programme.
16 December 2020
Researchers at Northwestern University and the Oxford Internet Institute, University of Oxford, are proud to announce the stable release of the Network Canvas suite of tools for collecting social network data.
30 April 2018
The Motley Fool, 04 October 2023
Welcome to the era of social media paywall. Article includes commentary from OII expert Bernie Hogan.
Oxford Sparks Big Questions Podcast, 25 January 2023
Are we really just one VR headset away from paradise? Or is the metaverse doomed before it's even really got off the ground? We chat to Dr Bernie Hogan from the OII to find out if Big Tech's confidence in the metaverse might be misplaced.
BBC Radio 4, 18 April 2022
VOICE NOTES Seven billion WhatsApp voice notes are sent every day but are they an effective means of communication? Cristina Criddle, tech reporter for the FT and Bernie Hogan, senior research fellow at the Oxford Internet Institute, discuss.
This course will familiarize students with a variety of techniques for cleaning and shaping data.
This is a capstone course for students in their final term. It is an opportunity for the whole cohort to reconvene and present their thesis work in progress to the group. Additionally, seminars may include advice on best practices in research and life after the MSc.
This course is a four week intensive primer to get people up to speed on programming in the Python programming language for use with data science. It covers basics of claim-making, analysis, and Python for data science.