@inproceedings{f10e9ebaa9464736aa051778b3faada9,
title = "LikeMiner: A system for mining the power of'like'in social media networks",
abstract = "Social media is becoming increasingly ubiquitous and popular on the Internet. Due to the huge popularity of social media websites, such as Facebook, Twitter, YouTube and Flickr, many companies or public figures are now active in maintaining pages on those websites to interact with online users, attracting a large number of fans/followers by posting interesting objects, e.g., (product) photos/videos and text messages.'Like'has now become a very popular social function by allowing users to express their like of certain objects. It provides an accurate way of estimating user interests and an effective way of sharing/promoting information in social media. In this demo, we propose a system called LikeMiner to mine the power of'like'in social media networks. We introduce a heterogeneous network model for social media with'likes', and propose'like'mining algorithms to estimate representativeness and influence of objects. The implemented prototype system demonstrates the effectiveness of the proposed approach using the large scale Facebook data.",
keywords = "Data mining, Influence analysis, Information network, Like, Ranking, Recommendation, Social media",
author = "Xin Jin and Chi Wang and Jiebo Luo and Xiao Yu and Jiawei Han",
year = "2011",
doi = "10.1145/2020408.2020528",
language = "English (US)",
isbn = "9781450308137",
series = "Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",
publisher = "Association for Computing Machinery",
pages = "753--756",
booktitle = "Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD'11",
address = "United States",
note = "17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2011 ; Conference date: 21-08-2011 Through 24-08-2011",
}