SRAD community updates

Systematic Identification of Tortured Phrases

In our July meeting, Alexandre Clausse shared his doctoral research focused on the systematic identification of tortured phrases. Using the Dimensions API full-text search, and a self-built application, Alex is working to uncover additional tortured phrases and detect their prevalence in scientific literature over time.

This work builds on and contributes to the Problematic Paper Screener, developed by Alex’s supervisor, Guillaume Cabanac, which identifies papers containing tortured phrases (more than five, or obviously tortured, phrases).

Alexandre Clausse is a doctoral candidate at the University of Toulouse.

Simulating citation behavior and cartels with agent-based models

Our June meeting featured George Chacko, who presented his group’s work utilizing Agent-Based Models (ABM) to simulate human citation behaviors and citation cartels in artificial networks. The simulations revealed a fascinating “quenching effect,” showing that the introduction of “superstar” high-fitness nodes actively siphons citation counts away from average papers, operating as a zero-sum game within a scientific domain.

Furthermore, by modeling artificial citation cartels, the data showed that colluding members would achieve a distinct early and cumulative citation advantage.

The meeting concluded with an open invitation for the SRAD community to access and experiment with the shared simulation code on GitHub.

George Chacko is a research associate professor at the Siebel School of Computing and Data Science and the Executive Director of Research Analytics at the Grainger College of Engineering (University of Illinois Urbana-Champaign).

Applying economic complexity models to global science discussions

This month, Yajie Wang presented a fascinating project that applies the Economics Complexity Index (ECI) to measure the complexity of public attention to science on X/Twitter. Analyzing a massive dataset of 54.6 million posts, the research demonstrated that raw post/tweet volume does not inherently equal attention complexity.

The findings sparked a great discussion on how language barriers and platform preferences can create a divide between a country’s scientific knowledge production and its footprint in global digital discussions.

For data access, Kathryn Weber-Boer provided guidance on navigating API limits, advising users to utilize the query_iterative function for up to 50,000 records or to pull researcher information directly from Google BigQuery using Python.

Why citation counts fail to represent the flow of attention to research

April’s session highlighted Jessica Rodrigues‘ doctoral project on representing attention to research, the evidence by which its societal impact is assessed. She argued that counts like total citations encode the volume of attention research outputs receive online, discarding the contexts that give it meaning: what is said, who says it, and what it is about.

Her work instead represents attention as flows, using Altmetric and Dimensions data, and tests whether that representation evidences impact better than counting does. The first article, accepted at STI 2026, is available at https://arxiv.org/abs/2606.05895

During our technical Q&A, we highlighted the limitation of 1.5 million posts from X per month, using the Altmetric APIs. A question was also raised about the research classifications for grants in Dimensions, which Kathryn confirmed are derived from classification of the text of the grant abstract, using a function much like the DSL classify function.

Jessica Rodrigues is a doctoral researcher at the Oxford Internet Institute, University of Oxford, and Lead Data Scientist.

Testing the causal impact of social media on research visibility

In March, Kim Yi Dionne shared her team’s ongoing multi-arm field experiment investigating the causal impact of scientific communication on research impact. To move beyond purely correlational data, the project randomly assigned political science articles to five distinct communication treatments, including Reddit posts, long social media threads, blogs, and short-form videos like TikToks and Reels.

The discussion addressed structural constraints in academia, the immense labor required to create digestible scientific content, and the potential safety risks for researchers online.

Measuring the impact penalty when researchers explore new fields

This month’s meeting featured an insightful presentation by Yian Yin on “The pivot penalty in research,” which explored the dynamics of researchers exploring new areas versus exploiting existing knowledge. The study revealed that larger topic pivots are systematically associated with lower citation impacts, demonstrating a clear “pivot penalty”.

On the technical side, the group tackled data linking challenges; Kathryn Weber-Boer shared a SQL query for Google BigQuery designed to help users effectively link and deduplicate book, monograph, and chapter records between the Altmetric and Dimensions datasets.