What is beautiful is not always good: influence of machine learning-derived photo attractiveness on intention to initiate social interactions in mobile dating applications
The popularity of mobile dating applications has reconstructed how people initiate new romantic relationships. Photo attractiveness, the most prominent information provided in the online dating context before social interactions, has attracted considerable attention but reached inconsistent conclusi...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2021-04-01
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| Series: | Connection Science |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/09540091.2020.1814204 |
| _version_ | 1797684072732950528 |
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| author | Ping Gao Xiaolun Wang Hong Chen Weihui Dai Hong Ling |
| author_facet | Ping Gao Xiaolun Wang Hong Chen Weihui Dai Hong Ling |
| author_sort | Ping Gao |
| collection | DOAJ |
| description | The popularity of mobile dating applications has reconstructed how people initiate new romantic relationships. Photo attractiveness, the most prominent information provided in the online dating context before social interactions, has attracted considerable attention but reached inconsistent conclusions. By considering the location, gender, and attractiveness difference between each dyad of participants (hunter and target) together, this study attempts to re-examine the contingent impact of physical attractiveness in initiating social interactions. Multi-methods (machine-learning and panel logistic regression) were used to empirically analyse the large-scale field data. The results show that: (1) A target’s photo attractiveness can promote a hunter’s willingness to leave a message; (2) The impact of photo attractiveness will be attenuated when two users have a larger location difference; (3) Male users are more likely to be impacted by photo attractiveness in their social interactions than female users; (4) A hunter with low attractiveness is inclined to initiate social interactions with a more attractive target; whereas a hunter with high attractiveness does not. This study deepens the theoretical implications in relevant fields, provides new methodology insight, and offers personalised marketing strategies for mobile dating applications. |
| first_indexed | 2024-03-12T00:24:05Z |
| format | Article |
| id | doaj.art-6b701c5a77564521bad7d4b631113fbc |
| institution | Directory Open Access Journal |
| issn | 0954-0091 1360-0494 |
| language | English |
| last_indexed | 2024-03-12T00:24:05Z |
| publishDate | 2021-04-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Connection Science |
| spelling | doaj.art-6b701c5a77564521bad7d4b631113fbc2023-09-15T10:47:59ZengTaylor & Francis GroupConnection Science0954-00911360-04942021-04-0133232134010.1080/09540091.2020.18142041814204What is beautiful is not always good: influence of machine learning-derived photo attractiveness on intention to initiate social interactions in mobile dating applicationsPing Gao0Xiaolun Wang1Hong Chen2Weihui Dai3Hong Ling4School of Management, Fudan UniversitySchool of Economics and Management, Nanjing University of Science and TechnologyChina Department of Digital Platform, Ping An TechnologySchool of Management, Fudan UniversitySchool of Management, Fudan UniversityThe popularity of mobile dating applications has reconstructed how people initiate new romantic relationships. Photo attractiveness, the most prominent information provided in the online dating context before social interactions, has attracted considerable attention but reached inconsistent conclusions. By considering the location, gender, and attractiveness difference between each dyad of participants (hunter and target) together, this study attempts to re-examine the contingent impact of physical attractiveness in initiating social interactions. Multi-methods (machine-learning and panel logistic regression) were used to empirically analyse the large-scale field data. The results show that: (1) A target’s photo attractiveness can promote a hunter’s willingness to leave a message; (2) The impact of photo attractiveness will be attenuated when two users have a larger location difference; (3) Male users are more likely to be impacted by photo attractiveness in their social interactions than female users; (4) A hunter with low attractiveness is inclined to initiate social interactions with a more attractive target; whereas a hunter with high attractiveness does not. This study deepens the theoretical implications in relevant fields, provides new methodology insight, and offers personalised marketing strategies for mobile dating applications.http://dx.doi.org/10.1080/09540091.2020.1814204photo attractivenesssocial interactionmobile dating applicationmachine learning |
| spellingShingle | Ping Gao Xiaolun Wang Hong Chen Weihui Dai Hong Ling What is beautiful is not always good: influence of machine learning-derived photo attractiveness on intention to initiate social interactions in mobile dating applications Connection Science photo attractiveness social interaction mobile dating application machine learning |
| title | What is beautiful is not always good: influence of machine learning-derived photo attractiveness on intention to initiate social interactions in mobile dating applications |
| title_full | What is beautiful is not always good: influence of machine learning-derived photo attractiveness on intention to initiate social interactions in mobile dating applications |
| title_fullStr | What is beautiful is not always good: influence of machine learning-derived photo attractiveness on intention to initiate social interactions in mobile dating applications |
| title_full_unstemmed | What is beautiful is not always good: influence of machine learning-derived photo attractiveness on intention to initiate social interactions in mobile dating applications |
| title_short | What is beautiful is not always good: influence of machine learning-derived photo attractiveness on intention to initiate social interactions in mobile dating applications |
| title_sort | what is beautiful is not always good influence of machine learning derived photo attractiveness on intention to initiate social interactions in mobile dating applications |
| topic | photo attractiveness social interaction mobile dating application machine learning |
| url | http://dx.doi.org/10.1080/09540091.2020.1814204 |
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