@inproceedings{5f5515eb601f4708acf1074704e637fe,
title = "JobMiner: A real-Time system for mining job-related patterns from social media",
abstract = "The various kinds of booming social media not only provide a platform where people can communicate with each other, but also spread useful domain information, such as career and job market information. For example, LinkedIn publishes a large amount of messages either about people who want to seek jobs or companies who want to recruit new members. By collecting information, we can have a better understanding of the job market and provide insights to job-seekers, companies and even decision makers. In this pa- per, we analyze the job information from the social network point of view. We first collect the job-related information from various social media sources. Then we construct an inter-company job-hopping network, with the vertices de- noting companies and the edges denoting flow of personnel between companies. We subsequently employ graph mining techniques to mine influential companies and related company groups based on the job-hopping network model. Demonstration on LinkedIn data shows that our system Job- Miner can provide a better understanding of the dynamic processes and a more accurate identification of important entities in the job market.",
keywords = "Graph mining, Influence analysis, Job market, Social media, Temporal network",
author = "Yu Cheng and Yusheng Xie and Zhengzhang Chen and Ankit Agrawal and Alok Choudhary and Songtao Guo",
note = "Publisher Copyright: Copyright {\textcopyright} 2013 ACM. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.; 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2013 ; Conference date: 11-08-2013 Through 14-08-2013",
year = "2013",
month = aug,
day = "11",
doi = "10.1145/2487575.2487704",
language = "English (US)",
series = "Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",
publisher = "Association for Computing Machinery",
pages = "1450--1453",
editor = "Rajesh Parekh and Jingrui He and Inderjit, {Dhillon S.} and Paul Bradley and Yehuda Koren and Rayid Ghani and Senator, {Ted E.} and Grossman, {Robert L.} and Ramasamy Uthurusamy",
booktitle = "KDD 2013 - 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining",
}