Who are the "Heroes of CRISPR"? Public science communication on Wikipedia and the challenge of micro-notability.

Wikipedia's influence in shaping public perceptions of science underscores the significance of scientists being recognized on the platform, as it can impact their careers. Although Wikipedia offers guidelines for determining when a scientist qualifies for their own article, it currently lacks guidance regarding whether a scientist should be acknowledged in articles related to the innovation processes to which they have contributed. To explore how Wikipedia addresses this issue of scientific "micro-notability," we introduce a digital method called Name Edit Analysis, enabling us to quantitatively and qualitatively trace mentions of scientists within Wikipedia's articles.

A diachronic perspective on citation latency in Wikipedia articles on CRISPR/Cas-9: an exploratory case study.

This paper analyzes Wikipedia's representation of the Nobel Prize winning CRISPR/Cas9 technology, a method for gene editing. We propose and evaluate different heuristics to match publications from several publication corpora against Wikipedia's central article on CRISPR and against the complete Wikipedia revision history in order to retrieve further Wikipedia articles relevant to the topic and to analyze Wikipedia's referencing patterns. We explore to what extent the selection of referenced literature of Wikipedia's central article on CRISPR adheres to scientific standards and inner-scientific perspectives by assessing its overlap with (1) the Web of Science (WoS) database, (2) a WoS-based field-delineated corpus, (3) highly-cited publications within this corpus, and (4) publications referenced by field-specific reviews.

A large dataset of scientific text reuse in Open-Access publications.

We present the Webis-STEREO-21 dataset, a massive collection of Scientific Text Reuse in Open-access publications. It contains 91 million cases of reused text passages found in 4.2 million unique open-access publications.

On Textual Analysis and Machine Learning for Cyberstalking Detection.

Cyber security has become a major concern for users and businesses alike. Cyberstalking and harassment have been identified as a growing anti-social problem. Besides detecting cyberstalking and harassment, there is the need to gather digital evidence, often by the victim.

WORDGRAPH: Keyword-in-Context Visualization for NETSPEAK's Wildcard Search.

The WORDGRAPH helps writers in visually choosing phrases while writing a text. It checks for the commonness of phrases and allows for the retrieval of alternatives by means of wildcard queries. To support such queries, we implement a scalable retrieval engine, which returns high-quality results within milliseconds using a probabilistic retrieval strategy.