Zobrazeno 1 - 10
of 35
pro vyhledávání: '"Cruickshank, Iain J."'
Public opinion of military organizations significantly influences their ability to recruit talented individuals. As recruitment efforts increasingly extend into digital spaces like social media, it becomes essential to assess the stance of social med
Externí odkaz:
http://arxiv.org/abs/2403.03334
Autor:
Benson, Seth P., Cruickshank, Iain J.
Media bias has been extensively studied by both social and computational sciences. However, current work still has a large reliance on human input and subjective assessment to label biases. This is especially true for cable news research. To address
Externí odkaz:
http://arxiv.org/abs/2310.09166
Stance classification, the task of predicting the viewpoint of an author on a subject of interest, has long been a focal point of research in domains ranging from social science to machine learning. Current stance detection methods rely predominantly
Externí odkaz:
http://arxiv.org/abs/2309.13734
With the rise of phenomena like `fake news' and the growth of heavily-biased media ecosystems, there has been increased attention on understanding and evaluating media bias. Of particular note in the evaluation of media bias is writing style bias, wh
Externí odkaz:
http://arxiv.org/abs/2305.13098
Autor:
Berenbeim, Alexander M., Cruickshank, Iain J., Jha, Susmit, Thomson, Robert H., Bastian, Nathaniel D.
Quantitative characterizations and estimations of uncertainty are of fundamental importance in optimization and decision-making processes. Herein, we propose intuitive scores, which we call certainty and doubt, that can be used in both a Bayesian and
Externí odkaz:
http://arxiv.org/abs/2303.14568
Publikováno v:
Terrorism and Political Violence, 0(0), 1-20 (2021)
Capturing dynamics of operational similarity among terrorist groups is critical to provide actionable insights for counter-terrorism and intelligence monitoring. Yet, in spite of its theoretical and practical relevance, research addressing this probl
Externí odkaz:
http://arxiv.org/abs/2112.07998
We introduce a novel method for analyzing person-to-person content influence on Twitter. Using an Ego-Alter framework and Granger Causality, we examine President Donald Trump (the Ego) and the people he retweets (Alters) as a case study. We find that
Externí odkaz:
http://arxiv.org/abs/2110.04899
The spread of coronavirus and anti-vaccine conspiracies online hindered public health responses to the pandemic. We examined the content of external articles shared on Twitter from February to June 2020 to understand how conspiracy theories and fake
Externí odkaz:
http://arxiv.org/abs/2107.09183
The COVID-19 pandemic has produced a flurry of online activity on social media sites. As such, analysis of social media data during the COVID-19 pandemic can produce unique insights into discussion topics and how those topics evolve over the course o
Externí odkaz:
http://arxiv.org/abs/2008.01139
Autor:
Cruickshank, Iain J.
Publikováno v:
Phalanx, 2022 Apr 01. 55(1), 32-36.
Externí odkaz:
https://www.jstor.org/stable/27116807
