Zobrazeno 1 - 10
of 564
pro vyhledávání: '"Kathleen M. Carley"'
Publikováno v:
EPJ Data Science, Vol 13, Iss 1, Pp 1-13 (2024)
Abstract This paper examines Russia’s propaganda discourse on Twitter during the 2022 invasion of Ukraine. The study employs network analysis, natural language processing (NLP) techniques, and qualitative analysis to identify key communities and na
Externí odkaz:
https://doaj.org/article/e9a58af959be4d88bd809716d606572f
Autor:
Scott Leo Renshaw, Kathleen M. Carley
Publikováno v:
Emerging Trends in Drugs, Addictions, and Health, Vol 4, Iss , Pp 100154- (2024)
As society grapples with the emerging significance and implications of Large Language Models (LLMs), such as OpenAI’s ChatGPT, or Google’s Gemini, as well as other advancements in modern generative Artificial Intelligence (AI), it is crucial to r
Externí odkaz:
https://doaj.org/article/c4c0dd65e1b049c2837adaf231e5d7dd
Publikováno v:
EPJ Data Science, Vol 12, Iss 1, Pp 1-28 (2023)
Abstract As digitalization increases, countries employ digital diplomacy, harnessing digital resources to project their desired image. Digital diplomacy also encompasses the interactivity of digital platforms, providing a trove of public opinion that
Externí odkaz:
https://doaj.org/article/aa7b5f4dae644e438c0fcfbfc4af8ec4
Publikováno v:
Social Media + Society, Vol 10 (2024)
News journalism has evolved from traditional print media to social media, with a large proportion of readers consuming their news via digital means. Through an analysis of over 1.3 million posts across three social media platforms (Facebook, Twitter,
Externí odkaz:
https://doaj.org/article/82213612458342fa9a589e2d4956dd08
Publikováno v:
BMC Digital Health, Vol 1, Iss 1, Pp 1-10 (2023)
Abstract Background Online infodemics have represented a major obstacle to the offline success of public health interventions during the COVID-19 pandemic. Offline contexts have likewise fueled public susceptibility to online infodemics. We combine a
Externí odkaz:
https://doaj.org/article/d97fce27b8054899a42be54a67b99a4e
Publikováno v:
Frontiers in Big Data, Vol 6 (2023)
Externí odkaz:
https://doaj.org/article/783ceb4b97004e4eb4e4a4ed61d51c7d
Autor:
Daniele Bellutta, Kathleen M. Carley
Publikováno v:
Journal of Big Data, Vol 10, Iss 1, Pp 1-17 (2023)
Abstract Democracies around the world face the threat of manipulation of their electorates via coordinated online influence campaigns. Researchers have responded by developing valuable methods for finding automated accounts and identifying false info
Externí odkaz:
https://doaj.org/article/b867021f64094770848a7e2df0d44e44
Publikováno v:
IEEE Access, Vol 11, Pp 19073-19092 (2023)
Data science techniques are powerful tools for extracting knowledge from large datasets. Analyzing the job market by classifying online job advertisements (ads) has recently received much attention. Various approaches for multi-label classification (
Externí odkaz:
https://doaj.org/article/dff89190df5440a39dd540b678faea78
Publikováno v:
Applied Network Science, Vol 8, Iss 1, Pp 1-22 (2023)
Abstract Social media has provided a citizen voice, giving rise to grassroots collective action, where users deploy a concerted effort to disseminate online narratives and even carry out offline protests. Sometimes these collective action are aided b
Externí odkaz:
https://doaj.org/article/3f6c017c3585460d8f9b1b92e864af73
Publikováno v:
Frontiers in Big Data, Vol 6 (2023)
IntroductionFrance has seen two key protests within the term of President Emmanuel Macron: one in 2020 against Islamophobia, and another in 2023 against the pension reform. During these protests, there is much chatter on online social media platforms
Externí odkaz:
https://doaj.org/article/dcca2f0983a74bdc90ef3c15e314364f