57 research outputs found
Automated Influence and the Challenge of Cognitive Security
Advances in AI are powering increasingly precise and widespread computational propaganda, posing serious threats to national security. The military and intelligence communities are starting to discuss ways to engage in this space, but the path forward is still unclear. These developments raise pressing ethical questions, about which existing ethics frameworks are silent. Understanding these challenges through the lens of ācognitive security,ā we argue, offers a promising approach
A Graph Theoretical Method for Partial Ordering of Alkanes
The topological Zagreb index M1 introduces an ordering on the set of alkanes. Recently, modified Zagreb indices Ī»M1 have been proposed, and it is noted that they differently order alkanes. In this paper, the level of consistency between these orders is analyzed. A new partial order >- as the intersection of all partial orders Ī»M1 (where m is at least 2) is introduced and its properties are analyzed
Can Large Language Models Discern Evidence for Scientific Hypotheses? Case Studies in the Social Sciences
Hypothesis formulation and testing are central to empirical research. A
strong hypothesis is a best guess based on existing evidence and informed by a
comprehensive view of relevant literature. However, with exponential increase
in the number of scientific articles published annually, manual aggregation and
synthesis of evidence related to a given hypothesis is a challenge. Our work
explores the ability of current large language models (LLMs) to discern
evidence in support or refute of specific hypotheses based on the text of
scientific abstracts. We share a novel dataset for the task of scientific
hypothesis evidencing using community-driven annotations of studies in the
social sciences. We compare the performance of LLMs to several state-of-the-art
benchmarks and highlight opportunities for future research in this area. The
dataset is available at
https://github.com/Sai90000/ScientificHypothesisEvidencing.gi
A Graph Theoretical Method for Partial Ordering of Alkanes
The topological Zagreb index M1 introduces an ordering on the set of alkanes. Recently, modified Zagreb indices Ī»M1 have been proposed, and it is noted that they differently order alkanes. In this paper, the level of consistency between these orders is analyzed. A new partial order >- as the intersection of all partial orders Ī»M1 (where m is at least 2) is introduced and its properties are analyzed
Effects of Online Self-Disclosure on Social Feedback During the COVID-19 Pandemic
We investigate relationships between online self-disclosure and received
social feedback during the COVID-19 crisis. We crawl a total of 2,399 posts and
29,851 associated comments from the r/COVID19_support subreddit and manually
extract fine-grained personal information categories and types of social
support sought from each post. We develop a BERT-based ensemble classifier to
automatically identify types of support offered in users' comments. We then
analyze the effect of personal information sharing and posts' topical, lexical,
and sentiment markers on the acquisition of support and five interaction
measures (submission scores, the number of comments, the number of unique
commenters, the length and sentiments of comments). Our findings show that: 1)
users were more likely to share their age, education, and location information
when seeking both informational and emotional support, as opposed to pursuing
either one; 2) while personal information sharing was positively correlated
with receiving informational support when requested, it did not correlate with
emotional support; 3) as the degree of self-disclosure increased, information
support seekers obtained higher submission scores and longer comments, whereas
emotional support seekers' self-disclosure resulted in lower submission scores,
fewer comments, and fewer unique commenters; 4) post characteristics affecting
social feedback differed significantly based on types of support sought by post
authors. These results provide empirical evidence for the varying effects of
self-disclosure on acquiring desired support and user involvement online during
the COVID-19 pandemic. Furthermore, this work can assist support seekers hoping
to enhance and prioritize specific types of social feedback
Perspectives from India: Challenges and Opportunities for Computational Tools to Enhance Confidence in Published Research
Over the past decade, a crisis of confidence in published scientific findings
has catalyzed widespread response from the research community, particularly in
the West. These responses have included policy discussions and changes to
existing practice as well as computational infrastructure to support and
evaluate research. Our work studies Indian researchers' awareness, perceptions,
and challenges around research integrity. We explore opportunities for
Artificial Intelligence (AI)-powered tools to evaluate reproducibility and
replicability, centering cultural perspectives. We discuss requirements for
such tools, including signals within papers and metadata to be included, and
system hybridity (fully-AI vs. collaborative human-AI). We draw upon 19
semi-structured interviews and 72 follow-up surveys with researchers at
universities throughout India. Our findings highlight the need for
computational tools to contextualize confidence in published research. In
particular, researchers prefer approaches that enable human-AI collaboration.
Additionally, our findings emphasize the shortcomings of current incentive
structures for publication, funding, and promotion
Extraction and Evaluation of Statistical Information from Social and Behavioral Science Papers
With substantial and continuing increases in the number of published papers across the scientific literature, development of reliable approaches for automated discovery and assessment of published findings is increasingly urgent. Tools which can extract critical information from scientific papers and metadata can support representation and reasoning over existing findings, and offer insights into replicability, robustness and generalizability of specific claims. In this work, we present a pipeline for the extraction of statistical information (p-values, sample size, number of hypotheses tested) from full-text scientific documents. We validate our approach on 300 papers selected from the social and behavioral science literatures, and suggest directions for next steps
- ā¦