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| Content Provider | ACM Digital Library |
|---|---|
| Author | Han, Weili Pang, Jun Ni, Minyue Zhang, Yang |
| Abstract | Hashtags, created by social network users, have gained a huge popularity in recent years. As a kind of metatag for organizing information, hashtags in online social networks, especially in Instagram, have greatly facilitated users' interactions. In recent years, academia starts to use hashtags to reshape our understandings on how users interact with each other. #like4like is one of the most popular hashtags in Instagram with more than 290 million photos appended with it, when a publisher uses #like4like in one photo, it means that he will like back photos of those who like this photo. Different from other hashtags, #like4like implies an interaction between a photo's publisher and a user who likes this photo, and both of them aim to attract likes in Instagram. In this paper, we study whether #like4like indeed serves the purpose it is created for, i.e., will #like4like provoke more likes? We first perform a general analysis of #like4like with 1.8 million photos collected from Instagram, and discover that its quantity has dramatically increased by 1,300 times from 2012 to 2016. Then, we study whether #like4like will attract likes for photo publishers; results show that it is not #like4like but actually photo contents attract more likes, and the lifespan of a #like4like photo is quite limited. In the end, we study whether users who like #like4like photos will receive likes from #like4like publishers. However, results show that more than 90% of the publishers do not keep their promises, i.e., they will not like back others who like their #like4like photos; and for those who keep their promises, the photos which they like back are often randomly selected. |
| Starting Page | 179 |
| Ending Page | 186 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781450349512 |
| DOI | 10.1145/3106426.3106460 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2017-08-23 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Social media behavior Hashtags Social networks Data mining |
| Content Type | Text |
| Resource Type | Article |
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