Facing Up to the Media: Walter Ong and the Embrace of Technology

General photograph of J. Stevens' rides building up, taken J. Stevens' Fair, 20 June 1961 general view. See Leeson's notebook 9, pages 92-95 for notes

Rethinking Research Partnerships: Discussion Guide and Toolkit

In recent years, there has been a drive towards research collaboration between academics and international non-governmental organisations (INGOs). These new partnerships offer exciting opportunities to improve learning and practice in international development, leading to innovation and deepened understandings of the world and, ultimately, a better impact on poverty eradication. However, they also present considerable challenges. How do organisations with different structures, goals and interests collaborate? Can they work together productively around these differences? What tensions exist and what is the impact of these? How is power distributed and which voices are amplified or lost in the process? This guide does not seek to answer these questions, but offers a way of exploring them. It is aimed at people and organisations that are considering embarking on a research collaboration, or are already working in partnership. It introduces some of the key issues that arise when working collaboratively, and suggests tools and activities to help you to critically reflect on them. The guide is aimed at those at the forefront of these partnerships – academics, INGO staff and their respective institutions. However, the content will also be of relevance to funders and others seeking to support or encourage collaborative research approaches. This guide is a toolkit for critical reflection, rooted in the idea that research partnerships must be entered into with care. Attention needs to be given to contexts, power relations and the different interests involved in order to successfully deliver truly collaborative knowledge generation that serves everyone’s interests. The risks are real – partnerships without serious considerations of the power dynamics risk reaffirming certain interests and voices and marginalising others, particularly those already experiencing structural disadvantage, undermining the real benefit that these partnerships can bring. In addition, they can end up placing unfunded and unsupported burdens on particular individuals or organisations, and reinforce existing structures that constrain the intended learning and growth

Bots, Seeds and People: Web Archives as Infrastructure

The field of web archiving provides a unique mix of human and automated agents collaborating to achieve the preservation of the web. Centuries old theories of archival appraisal are being transplanted into the sociotechnical environment of the World Wide Web with varying degrees of success. The work of the archivist and bots in contact with the material of the web present a distinctive and understudied CSCW shaped problem. To investigate this space we conducted semi-structured interviews with archivists and technologists who were directly involved in the selection of content from the web for archives. These semi-structured interviews identified thematic areas that inform the appraisal process in web archives, some of which are encoded in heuristics and algorithms. Making the infrastructure of web archives legible to the archivist, the automated agents and the future researcher is presented as a challenge to the CSCW and archival community

A rule dynamics approach to event detection in Twitter with its application to sports and politics

The increasing popularity of Twitter as social network tool for opinion expression as well as informa- tion retrieval has resulted in the need to derive computational means to detect and track relevant top- ics/events in the network. The application of topic detection and tracking methods to tweets enable users to extract newsworthy content from the vast and somehow chaotic Twitter stream. In this paper, we ap- ply our technique named Transaction-based Rule Change Mining to extract newsworthy hashtag keywords present in tweets from two different domains namely; sports (The English FA Cup 2012) and politics (US Presidential Elections 2012 and Super Tuesday 2012). Noting the peculiar nature of event dynamics in these two domains, we apply different time-windows and update rates to each of the datasets in order to study their impact on performance. The performance effectiveness results reveal that our approach is able to accurately detect and track newsworthy content. In addition, the results show that the adaptation of the time-window exhibits better performance especially on the sports dataset, which can be attributed to the usually shorter duration of football events