Analysis of HIV high-risk population characteristics with Baidu Tieba data
The textual content and temporal pattern of online activities for users gathered in the “Fear of HIV Bar” of Baidu Tieba were analyzed. LDA topic model was used to analyze the main differences between topics discussed among HIV-infected people and non-HIV-infected people. A machine learning method b...
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| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | zho |
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China InfoCom Media Group
2019-01-01
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| Series: | 大数据 |
| Subjects: | |
| Online Access: | http://www.j-bigdataresearch.com.cn/thesisDetails#10.11959/j.issn.2096-0271.2019008 |
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| _version_ | 1850213370059292672 |
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| author | Shiyao XIAO Wei LYU Saran CHEN Shuo QIN Ge HUANG Mengsi CAI Yuejin TAN Xu TAN Xin LU |
| author_facet | Shiyao XIAO Wei LYU Saran CHEN Shuo QIN Ge HUANG Mengsi CAI Yuejin TAN Xu TAN Xin LU |
| author_sort | Shiyao XIAO |
| collection | DOAJ |
| description | The textual content and temporal pattern of online activities for users gathered in the “Fear of HIV Bar” of Baidu Tieba were analyzed. LDA topic model was used to analyze the main differences between topics discussed among HIV-infected people and non-HIV-infected people. A machine learning method based on key words was used to distinguish the sexual orientation of users who start a discussion in “Fear of HIV Bar”, and calculate the epidemic rate of HIV among groups with different sexual orientations. The techniques used in this paper can be supplemented as an important tool for high-risk populations research. In addition, this paper can be applied to assess the epidemic of HIV in populations with different sexual orientations by using machine learning technique to intelligently classify the sexual orientation of a user, which is of great significance for the public health agencies. |
| format | Article |
| id | doaj-art-ffa8f426258941a7a9c765c9d08de1ee |
| institution | OA Journals |
| issn | 2096-0271 |
| language | zho |
| publishDate | 2019-01-01 |
| publisher | China InfoCom Media Group |
| record_format | Article |
| series | 大数据 |
| spelling | doaj-art-ffa8f426258941a7a9c765c9d08de1ee2025-08-20T02:09:08ZzhoChina InfoCom Media Group大数据2096-02712019-01-015201900859532690Analysis of HIV high-risk population characteristics with Baidu Tieba dataShiyao XIAOWei LYUSaran CHENShuo QINGe HUANGMengsi CAIYuejin TANXu TANXin LUThe textual content and temporal pattern of online activities for users gathered in the “Fear of HIV Bar” of Baidu Tieba were analyzed. LDA topic model was used to analyze the main differences between topics discussed among HIV-infected people and non-HIV-infected people. A machine learning method based on key words was used to distinguish the sexual orientation of users who start a discussion in “Fear of HIV Bar”, and calculate the epidemic rate of HIV among groups with different sexual orientations. The techniques used in this paper can be supplemented as an important tool for high-risk populations research. In addition, this paper can be applied to assess the epidemic of HIV in populations with different sexual orientations by using machine learning technique to intelligently classify the sexual orientation of a user, which is of great significance for the public health agencies.http://www.j-bigdataresearch.com.cn/thesisDetails#10.11959/j.issn.2096-0271.2019008online high-risk populations;MSM;HIV;LDA topic model;Baidu Tieba;machine learning |
| spellingShingle | Shiyao XIAO Wei LYU Saran CHEN Shuo QIN Ge HUANG Mengsi CAI Yuejin TAN Xu TAN Xin LU Analysis of HIV high-risk population characteristics with Baidu Tieba data 大数据 online high-risk populations;MSM;HIV;LDA topic model;Baidu Tieba;machine learning |
| title | Analysis of HIV high-risk population characteristics with Baidu Tieba data |
| title_full | Analysis of HIV high-risk population characteristics with Baidu Tieba data |
| title_fullStr | Analysis of HIV high-risk population characteristics with Baidu Tieba data |
| title_full_unstemmed | Analysis of HIV high-risk population characteristics with Baidu Tieba data |
| title_short | Analysis of HIV high-risk population characteristics with Baidu Tieba data |
| title_sort | analysis of hiv high risk population characteristics with baidu tieba data |
| topic | online high-risk populations;MSM;HIV;LDA topic model;Baidu Tieba;machine learning |
| url | http://www.j-bigdataresearch.com.cn/thesisDetails#10.11959/j.issn.2096-0271.2019008 |
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