The SDS Workshop is a space for SDS Hub participants to share work in progress, provide feedback on the work of other colleagues, and discuss project ideas.
Papers for each workshop will be circulated in advance for participants to review before each meeting. Meetings will be hybrid and Zoom links for each event will be circulated on the SDS Hub mailing list prior to the event. Details of upcoming workshops are below:
| Title | Author | Date and Time | Venue | Registration |
| Machine Learning Models for the Measurement of Media Criticism | Christopher Barrie | March 10 2023, 4pm-5.30pm | 1.15 Informatics Forum | Click here to register for the event |
| The Goldilocks effect: The “just right” writing style of the most-used global corporate responsibility frameworks | Adam Chalmers | November 2 2023, 2-3pm | CMB Meeting Room 4 | Click here to register for the event |
Workshop Details
Machine Learning Models for the Measurement of Media Criticism
Abstract: The ability of news media to criticize government is a core pillar of media freedom. Existing indices tend to use scoring criteria or expert surveys to develop over-time measures of media freedom. In this article, we use the largest existing dataset of Arabic-language news to evaluate how political reporting changes over the course of a successful and failed democratic transition. Using entirely unsupervised ALC word-embedding techniques, we demonstrate how to generate temporally granular measurements of media criticism that closely correlate with measurements derived from expert surveys for both Egypt and Tunisia. Crucially, the technique we propose is computationally inexpensive, effectively cost-free, and eminently scalable. In this, our work points to new possibilities in the monitoring and measurement of media capture within authoritarian and transitional settings.
Methods: Word-embedding; NLP; Transformers
The Goldilocks effect: The “just right” writing style of the most-used global corporate responsibility frameworks
Abstract: The 21st century has seen an explosive increase in the number of global corporate responsibility (GCR) frameworks—issued by international organizations (IOs)—that shape firms’ communications of their commitment to corporate social responsibility (CSR). Scholarship offers insight into the determinants of firms’ CSR communications at the firm, national, and sectoral levels. However, much less attention has been paid to understanding firms’ use of the GCR frameworks. Understanding firms’ choice of GCR frameworks offers an advance to the basis of firms’ CSR “talk.” This study offers a new line of inquiry as it examines how firms’ use of GCR frameworks may be affected by how GCR frameworks are written. It does this by combining theoretical insights from affordance theory and computational linguistics. It employs natural language processing methods to examine 320 firms’ CSR communications (which totals 4,025 documents) for “re-use” of the GCR framework text. The study finds a “goldilocks effect” whereby firms’ use GCR frameworks is greatest when frameworks are written in language that is not too simple nor too complex. The implication is that policies should be written in clear, but neither overly simplistic nor jargon-heavy, language in order to boost firms’ engagement.
Methods: NLP