Abstract
This paper introduces the problem of determining whether people are located in the places they mention in their tweets. In particular, we investigate the role of text and images to solve this challenging problem. We present a new corpus of tweets that contain both text and images. Our analyses show that this problem is multimodal at its core: human judgments depend on whether annotators have access to the text, the image, or both. Experimental results show that a neural architecture that combines both modalities yields better results. We also conduct an error analysis to provide insights into why and when each modality is beneficial.- Anthology ID:
- 2022.coling-1.226
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 2561–2571
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.226
- DOI:
- Bibkey:
- Cite (ACL):
- Zhaomin Xiao and Eduardo Blanco. 2022. Are People Located in the Places They Mention in Their Tweets? A Multimodal Approach. In Proceedings of the 29th International Conference on Computational Linguistics, pages 2561–2571, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- Are People Located in the Places They Mention in Their Tweets? A Multimodal Approach (Xiao & Blanco, COLING 2022)
- Copy Citation:
- PDF:
- https://aclanthology.org/2022.coling-1.226.pdf
- Code
- zhaomin1995/coling2022_repo
Export citation
@inproceedings{xiao-blanco-2022-people,
title = "Are People Located in the Places They Mention in Their Tweets? A Multimodal Approach",
author = "Xiao, Zhaomin and
Blanco, Eduardo",
editor = "Calzolari, Nicoletta and
Huang, Chu-Ren and
Kim, Hansaem and
Pustejovsky, James and
Wanner, Leo and
Choi, Key-Sun and
Ryu, Pum-Mo and
Chen, Hsin-Hsi and
Donatelli, Lucia and
Ji, Heng and
Kurohashi, Sadao and
Paggio, Patrizia and
Xue, Nianwen and
Kim, Seokhwan and
Hahm, Younggyun and
He, Zhong and
Lee, Tony Kyungil and
Santus, Enrico and
Bond, Francis and
Na, Seung-Hoon",
booktitle = "Proceedings of the 29th International Conference on Computational Linguistics",
month = oct,
year = "2022",
address = "Gyeongju, Republic of Korea",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2022.coling-1.226",
pages = "2561--2571",
abstract = "This paper introduces the problem of determining whether people are located in the places they mention in their tweets. In particular, we investigate the role of text and images to solve this challenging problem. We present a new corpus of tweets that contain both text and images. Our analyses show that this problem is multimodal at its core: human judgments depend on whether annotators have access to the text, the image, or both. Experimental results show that a neural architecture that combines both modalities yields better results. We also conduct an error analysis to provide insights into why and when each modality is beneficial.",
}
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%0 Conference Proceedings %T Are People Located in the Places They Mention in Their Tweets? A Multimodal Approach %A Xiao, Zhaomin %A Blanco, Eduardo %Y Calzolari, Nicoletta %Y Huang, Chu-Ren %Y Kim, Hansaem %Y Pustejovsky, James %Y Wanner, Leo %Y Choi, Key-Sun %Y Ryu, Pum-Mo %Y Chen, Hsin-Hsi %Y Donatelli, Lucia %Y Ji, Heng %Y Kurohashi, Sadao %Y Paggio, Patrizia %Y Xue, Nianwen %Y Kim, Seokhwan %Y Hahm, Younggyun %Y He, Zhong %Y Lee, Tony Kyungil %Y Santus, Enrico %Y Bond, Francis %Y Na, Seung-Hoon %S Proceedings of the 29th International Conference on Computational Linguistics %D 2022 %8 October %I International Committee on Computational Linguistics %C Gyeongju, Republic of Korea %F xiao-blanco-2022-people %X This paper introduces the problem of determining whether people are located in the places they mention in their tweets. In particular, we investigate the role of text and images to solve this challenging problem. We present a new corpus of tweets that contain both text and images. Our analyses show that this problem is multimodal at its core: human judgments depend on whether annotators have access to the text, the image, or both. Experimental results show that a neural architecture that combines both modalities yields better results. We also conduct an error analysis to provide insights into why and when each modality is beneficial. %U https://aclanthology.org/2022.coling-1.226 %P 2561-2571
Markdown (Informal)
[Are People Located in the Places They Mention in Their Tweets? A Multimodal Approach](https://aclanthology.org/2022.coling-1.226) (Xiao & Blanco, COLING 2022)
- Are People Located in the Places They Mention in Their Tweets? A Multimodal Approach (Xiao & Blanco, COLING 2022)
ACL
- Zhaomin Xiao and Eduardo Blanco. 2022. Are People Located in the Places They Mention in Their Tweets? A Multimodal Approach. In Proceedings of the 29th International Conference on Computational Linguistics, pages 2561–2571, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.