A social media geolocation method based on comparative learning
Previous work on social media text-based geolocation focused on mapping language semantic space to geospatial space, which ignores the semantic correlation between social media texts and the distance correlation between geographical locations.To take advantage of these correlations, mCLF, a new unsu...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2023-08-01
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| Series: | Dianxin kexue |
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| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2023154/ |
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| author | Yongchang XU Shiduo HUANG Haojun AI |
| author_facet | Yongchang XU Shiduo HUANG Haojun AI |
| author_sort | Yongchang XU |
| collection | DOAJ |
| description | Previous work on social media text-based geolocation focused on mapping language semantic space to geospatial space, which ignores the semantic correlation between social media texts and the distance correlation between geographical locations.To take advantage of these correlations, mCLF, a new unsupervised multiple-level contrastive learning framework was proposed, three contrastive learning modules were designed: a semantic learning module, a location learning module, and a cross-learning module.Transformer encoder was used to obtain semantic representation of posts, utilizing unsupervised contrastive learning method to decrease the distance of semantic representations and location representations of posts with near locations, and then fine-tuned the model with supervised method for geographic location regression or classification outputs.Compared with five baseline methods, extensive experiments based on four datasets demonstrate the effectiveness of the proposed framework. |
| format | Article |
| id | doaj-art-766c479fb0e44a4f89fae2d4c067bf3c |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2023-08-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-766c479fb0e44a4f89fae2d4c067bf3c2025-01-15T02:58:17ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012023-08-0139586859562499A social media geolocation method based on comparative learningYongchang XUShiduo HUANGHaojun AIPrevious work on social media text-based geolocation focused on mapping language semantic space to geospatial space, which ignores the semantic correlation between social media texts and the distance correlation between geographical locations.To take advantage of these correlations, mCLF, a new unsupervised multiple-level contrastive learning framework was proposed, three contrastive learning modules were designed: a semantic learning module, a location learning module, and a cross-learning module.Transformer encoder was used to obtain semantic representation of posts, utilizing unsupervised contrastive learning method to decrease the distance of semantic representations and location representations of posts with near locations, and then fine-tuned the model with supervised method for geographic location regression or classification outputs.Compared with five baseline methods, extensive experiments based on four datasets demonstrate the effectiveness of the proposed framework.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2023154/social mediageolocationcontrastive learninginformation miningTransformer |
| spellingShingle | Yongchang XU Shiduo HUANG Haojun AI A social media geolocation method based on comparative learning Dianxin kexue social media geolocation contrastive learning information mining Transformer |
| title | A social media geolocation method based on comparative learning |
| title_full | A social media geolocation method based on comparative learning |
| title_fullStr | A social media geolocation method based on comparative learning |
| title_full_unstemmed | A social media geolocation method based on comparative learning |
| title_short | A social media geolocation method based on comparative learning |
| title_sort | social media geolocation method based on comparative learning |
| topic | social media geolocation contrastive learning information mining Transformer |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2023154/ |
| work_keys_str_mv | AT yongchangxu asocialmediageolocationmethodbasedoncomparativelearning AT shiduohuang asocialmediageolocationmethodbasedoncomparativelearning AT haojunai asocialmediageolocationmethodbasedoncomparativelearning AT yongchangxu socialmediageolocationmethodbasedoncomparativelearning AT shiduohuang socialmediageolocationmethodbasedoncomparativelearning AT haojunai socialmediageolocationmethodbasedoncomparativelearning |