Related papers: Comparing Disciplinary Classifications in SSH: Org…
The aim of the study was to assess and compare established search systems and approaches by using the search goal of identifying the first (as in oldest) nursing-related document, with reference to the first Swedish-affiliated document, in…
This paper proposes a classification framework aimed at identifying correlations between job ad requirements and transversal skill sets, with a focus on predicting the necessary skills for individual job descriptions using a deep learning…
Social media has provided a platform for users to gather and share information and stay updated with the news. Such networks also provide a platform to users where they can engage in conversations. However, such micro-blogging platforms…
This article presents a study that compares detected structural communities in a coauthorship network to the socioacademic characteristics of the scholars that compose the network. The coauthorship network was created from the bibliographic…
Authorship attribution is the process of identifying the author of a text. Approaches to tackling it have been conventionally divided into classification-based ones, which work well for small numbers of candidate authors, and…
When research groups are evaluated by an expert panel, it is an open question how one can determine the match between panel and research groups. In this paper, we outline two quantitative approaches that determine the cognitive distance…
With the increasing integration of visual and textual content in Social Networking Services (SNS), evaluating the multimodal capabilities of Large Language Models (LLMs) is crucial for enhancing user experience, content understanding, and…
Authorial clustering involves the grouping of documents written by the same author or team of authors without any prior positive examples of an author's writing style or thematic preferences. For authorial clustering on shorter texts…
Scholarly documents have a great degree of variation, both in terms of content (semantics) and structure (pragmatics). Prior work in scholarly document understanding emphasizes semantics through document summarization and corpus topic…
Comparative reasoning plays a crucial role in text preference prediction; however, large language models (LLMs) often demonstrate inconsistencies in their reasoning. While approaches like Chain-of-Thought improve accuracy in many other…
Humans are able to recognize structured relations in observation, allowing us to decompose complex scenes into simpler parts and abstract the visual world in multiple levels. However, such hierarchical reasoning ability of human perception…
Social scientists have shown that up to 50% if the content posted to a news article have no relation to its journalistic content. In this study we propose a classification algorithm to categorize user comments posted to a new article base…
We present a multi-channel database of overlapping speech for training, evaluation, and detailed analysis of source separation and extraction algorithms: SMS-WSJ -- Spatialized Multi-Speaker Wall Street Journal. It consists of artificially…
Bibliometric measures, such as total citations and h-index, have become a cornerstone for evaluating academic performance; however, these traditional metrics, being non-weighted, inadequately capture the nuances of individual contributions.…
Text classification stands as a cornerstone within the realm of Natural Language Processing (NLP), particularly when viewed through computer science and engineering. The past decade has seen deep learning revolutionize text classification,…
Contextualisation has proven to be effective in tailoring \linebreak search results towards the users' information need. While this is true for a basic query search, the usage of contextual session information during exploratory search…
The rapid adoption of large language models (LLMs) in scientific writing raises serious concerns regarding authorship integrity and the reliability of scholarly publications. Existing detection approaches mainly rely on document-level…
With the growing importance of sustainable development goals (SDGs), various labeling systems have emerged for effective monitoring and evaluation. This study assesses six labeling systems across 1.85 million documents at both paper level…
Collaboration networks arise when we map the connections between scientists which are formed through joint publications. These networks thus display the social structure of academia, and also allow conclusions about the structure of…
Large language models excel on objectively verifiable tasks such as math and programming, where evaluation reduces to unit tests or a single correct answer. In contrast, real-world enterprise work is often subjective and context-dependent:…