Chinese Celebrity Popularity Prediction on Instagram
| Autor: | Ting-Yi Su, 蘇庭毅 |
|---|---|
| Rok vydání: | 2018 |
| Druh dokumentu: | 學位論文 ; thesis |
| Popis: | 106 In recent years, social media become much more popular according to the increasing usage of smartphone and the advances in communication technology. People can communicate, share information with others and even self-promotion via social media. To people who live in the era, no one can totally stay away from social media. Enterprises, advertisers and internet celebrities can gain revenue by increasing their popularity among users of social media. Therefore, how to keep the exposure rate or even increase the popularity on social media has become an issue to them. We aim to predict popularity at 24th hour in advance by post content in this study. Our data is from Instagram which is a platform people can record and share their life by photos. It is a popular social media among teenagers due to its image-emphasizing sharing method. And our target users are people who are well-known in the real world. Promotion in social media can be a vital way to keep or increase their popularity for these people. By using SnowNLP, we can retrieve text sentiment from caption of a post. Then we use DeepSentiBank model as an extractor which can get image emotion and image content category. Combining these features with information of user account, we build models to predict popularity. Predicted popularity has 90.45% log scale accuracy on test set. Comparing our result with previous work, we have closer numbers to the actual popularity. Also, we regard popularity prediction as binary classification task which is popular versus unpopular and we obtain 88.71% accuracy on this classification task. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
|