Predicting and describing the use of generative AI in science-related information search: Insights from a multinational survey

Esther Greussing; Lars Guenther; Ayelet Baram-Tsabari; Shakked Dabran-Zivan; Evelyn Jonas; Inbal Klein-Avraham; Monika Taddicken; Becca Beets; Dominique Brossard; Anwesha Chakraborty; Torben Esbo Agergaard; Antoinette Fage-Butler; Chun Ju Huang; Kristian Hvidtfelt Nielsen; Siddharth Kankaria; Yin-Yueh Lo; Michelle Riedlinger; Hyunjin Jin Song

Predicting and describing the use of generative AI in science-related information search: Insights from a multinational survey

Esther Greussing, Lars Guenther, Ayelet Baram-Tsabari, Shakked Dabran-Zivan, Evelyn Jonas, Inbal Klein-Avraham, Monika Taddicken, Becca Beets, Dominique Brossard, Anwesha Chakraborty, Torben Esbo Agergaard, Antoinette Fage-Butler, Chun Ju Huang, Kristian Hvidtfelt Nielsen, Siddharth Kankaria, Yin-Yueh Lo, Michelle Riedlinger, Hyunjin Jin Song

Research output: Contribution to conference › Conference abstract for conference › Research › peer-review

Original language	English
Publication date	Apr 2024
Publication status	Published - Apr 2024
Event	Annual Conference of the “Science Communication” Division of the German Communication Association 2024 - University of Zürich, Zürich, Switzerland Duration: 6 Jun 2024 → 7 Jun 2024 https://www.ikmz.uzh.ch/en/aiscicomm24.html

Conference

Conference	Annual Conference of the “Science Communication” Division of the German Communication Association 2024
Location	University of Zürich
Country/Territory	Switzerland
City	Zürich
Period	06/06/2024 → 07/06/2024
Internet address	https://www.ikmz.uzh.ch/en/aiscicomm24.html

Access to Document

https://www.ikmz.uzh.ch/dam/jcr:f29f21aa-1025-4b39-b848-4aefbd13a781/AI&SCICOMM24_Book%20of%20Abstracts.pdf

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SCI-AI: Science Information Search with AI Technologies
Guenther, L. (PI), Greussing, E. (PI), Nielsen, K. H. (Participant), Fage-Butler, A. M. (Participant), Agergaard, T. E. (Participant), Song, H. (Participant), Joubert, M. (Participant), Lo, Y.-Y. (Participant), Brossard, D. (Participant), Baram-Tsabari, A. (Participant), Taddicken, M. (PI), Kankaria, S. (Participant) & Chakraborty, A. (Participant)
01/01/2023 → 31/12/2024
Project: Research

Cite this

Greussing, E., Guenther, L., Baram-Tsabari, A., Dabran-Zivan, S., Jonas, E., Klein-Avraham, I., Taddicken, M., Beets, B., Brossard, D., Chakraborty, A., Agergaard, T. E., Fage-Butler, A., Ju Huang, C., Nielsen, K. H., Kankaria, S., Lo, Y.-Y., Riedlinger, M., & Song, H. J. (2024). Predicting and describing the use of generative AI in science-related information search: Insights from a multinational survey. Abstract from Annual Conference of the “Science Communication” Division of the German Communication Association 2024, Zürich, Switzerland. https://www.ikmz.uzh.ch/dam/jcr:f29f21aa-1025-4b39-b848-4aefbd13a781/AI&SCICOMM24_Book%20of%20Abstracts.pdf

@conference{5e39a5723892467eb8e6be6d80e85064,

title = "Predicting and describing the use of generative AI in science-related information search: Insights from a multinational survey",

author = "Esther Greussing and Lars Guenther and Ayelet Baram-Tsabari and Shakked Dabran-Zivan and Evelyn Jonas and Inbal Klein-Avraham and Monika Taddicken and Becca Beets and Dominique Brossard and Anwesha Chakraborty and Agergaard, {Torben Esbo} and Antoinette Fage-Butler and {Ju Huang}, Chun and Nielsen, {Kristian Hvidtfelt} and Siddharth Kankaria and Yin-Yueh Lo and Michelle Riedlinger and Song, {Hyunjin Jin}",

year = "2024",

month = apr,

language = "English",

note = "Annual Conference of the “Science Communication” Division of the German Communication Association 2024, AISCICOMM24 ; Conference date: 06-06-2024 Through 07-06-2024",

url = "https://www.ikmz.uzh.ch/en/aiscicomm24.html",

}

Greussing, E, Guenther, L, Baram-Tsabari, A, Dabran-Zivan, S, Jonas, E, Klein-Avraham, I, Taddicken, M, Beets, B, Brossard, D, Chakraborty, A, Agergaard, TE , Fage-Butler, A, Ju Huang, C, Nielsen, KH, Kankaria, S, Lo, Y-Y, Riedlinger, M & Song, HJ 2024, 'Predicting and describing the use of generative AI in science-related information search: Insights from a multinational survey', Annual Conference of the “Science Communication” Division of the German Communication Association 2024, Zürich, Switzerland, 06/06/2024 - 07/06/2024. <https://www.ikmz.uzh.ch/dam/jcr:f29f21aa-1025-4b39-b848-4aefbd13a781/AI&SCICOMM24_Book%20of%20Abstracts.pdf>

Predicting and describing the use of generative AI in science-related information search: Insights from a multinational survey. / Greussing, Esther; Guenther, Lars; Baram-Tsabari, Ayelet et al.
2024. Abstract from Annual Conference of the “Science Communication” Division of the German Communication Association 2024, Zürich, Switzerland.

Research output: Contribution to conference › Conference abstract for conference › Research › peer-review

TY - ABST

T1 - Predicting and describing the use of generative AI in science-related information search

T2 - Annual Conference of the “Science Communication” Division of the German Communication Association 2024

AU - Greussing, Esther

AU - Guenther, Lars

AU - Baram-Tsabari, Ayelet

AU - Dabran-Zivan, Shakked

AU - Jonas, Evelyn

AU - Klein-Avraham, Inbal

AU - Taddicken, Monika

AU - Beets, Becca

AU - Brossard, Dominique

AU - Chakraborty, Anwesha

AU - Agergaard, Torben Esbo

AU - Fage-Butler, Antoinette

AU - Ju Huang, Chun

AU - Nielsen, Kristian Hvidtfelt

AU - Kankaria, Siddharth

AU - Lo, Yin-Yueh

AU - Riedlinger, Michelle

AU - Song, Hyunjin Jin

PY - 2024/4

Y1 - 2024/4

M3 - Conference abstract for conference

Y2 - 6 June 2024 through 7 June 2024

ER -

Predicting and describing the use of generative AI in science-related information search: Insights from a multinational survey

Conference

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SCI-AI: Science Information Search with AI Technologies

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