@inproceedings{jafari-etal-2023-longitudinal-study,
title = "A longitudinal study about gradual changes in the {I}ranian Online Public Sphere pre and post of {\textquoteleft}Mahsa Moment': Focusing on {T}witter",
author = "Jafari, Sadegh and
Fathi, Amin and
Hajizadegan, Abolfazl and
Kazemeini, Amirmohammad and
Eetemadi, Sauleh",
editor = "Tahmasebi, Nina and
Montariol, Syrielle and
Dubossarsky, Haim and
Kutuzov, Andrey and
Hengchen, Simon and
Alfter, David and
Periti, Francesco and
Cassotti, Pierluigi",
booktitle = "Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change",
month = dec,
year = "2023",
address = "Singapore",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.lchange-1.5/",
doi = "10.18653/v1/2023.lchange-1.5",
pages = "46--52",
abstract = "Mahsa Amini`s death shocked Iranian society. The effects of this event and the subsequent tragedies in Iran not only in realspace but also in cyberspace, including Twitter, were tremendous and unimaginable. We explore how Twitter has changed after Mahsa Amini`s death by analyzing the sentiments of Iranian users in the 90 days after this event. Additionally, we track the change in word meaning and each word`s neighboring words. Finally, we use word clustering methods for topic modeling."
}
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<abstract>Mahsa Amini‘s death shocked Iranian society. The effects of this event and the subsequent tragedies in Iran not only in realspace but also in cyberspace, including Twitter, were tremendous and unimaginable. We explore how Twitter has changed after Mahsa Amini‘s death by analyzing the sentiments of Iranian users in the 90 days after this event. Additionally, we track the change in word meaning and each word‘s neighboring words. Finally, we use word clustering methods for topic modeling.</abstract>
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%0 Conference Proceedings
%T A longitudinal study about gradual changes in the Iranian Online Public Sphere pre and post of ‘Mahsa Moment’: Focusing on Twitter
%A Jafari, Sadegh
%A Fathi, Amin
%A Hajizadegan, Abolfazl
%A Kazemeini, Amirmohammad
%A Eetemadi, Sauleh
%Y Tahmasebi, Nina
%Y Montariol, Syrielle
%Y Dubossarsky, Haim
%Y Kutuzov, Andrey
%Y Hengchen, Simon
%Y Alfter, David
%Y Periti, Francesco
%Y Cassotti, Pierluigi
%S Proceedings of the 4th Workshop on Computational Approaches to Historical Language Change
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore
%F jafari-etal-2023-longitudinal-study
%X Mahsa Amini‘s death shocked Iranian society. The effects of this event and the subsequent tragedies in Iran not only in realspace but also in cyberspace, including Twitter, were tremendous and unimaginable. We explore how Twitter has changed after Mahsa Amini‘s death by analyzing the sentiments of Iranian users in the 90 days after this event. Additionally, we track the change in word meaning and each word‘s neighboring words. Finally, we use word clustering methods for topic modeling.
%R 10.18653/v1/2023.lchange-1.5
%U https://aclanthology.org/2023.lchange-1.5/
%U https://doi.org/10.18653/v1/2023.lchange-1.5
%P 46-52
Markdown (Informal)
[A longitudinal study about gradual changes in the Iranian Online Public Sphere pre and post of ‘Mahsa Moment’: Focusing on Twitter](https://aclanthology.org/2023.lchange-1.5/) (Jafari et al., LChange 2023)
ACL