@inproceedings{16a4fb76ada94e869ea418f3b3b11abc,
title = "Understanding employee social media chatter with enterprise social pulse",
abstract = "The rise of social media in the enterprise has enabled new ways for employees to speak up and communicate openly with colleagues. This rich textual data can potentially be mined to better understand the opinions and sentiment of employees for the benefit of the organization. In this paper, we introduce Enterprise Social Pulse (ESP) - a tool designed to support analysts whose job involves understanding employee chatter. ESP aggregates and analyzes data from internal and external social media sources while respecting employee privacy. It surfaces the data through a user interface that supports organic results and keyword search, data segmentation and filtering, and several analytics and visualization features. An evaluation of ESP was conducted with 19 Human Resources professionals. Results from a survey and interviews with participants revealed the value and willingness to use ESP, but also surfaced challenges around deploying an employee social media listening solution in an organization.",
keywords = "Social analytics, Social listening, Social media, Workplace",
author = "Shami, {N. Sadat} and Jiang Yang and Laura Panc and Casey Dugan and Tristan Ratchford and Jamie Rasmussen and Yannick Assogba and Tal Steier and Todd Soule and Stela Lupushor and Werner Geyer and Ido Guy and Jonathan Ferrar",
year = "2014",
month = jan,
day = "1",
doi = "10.1145/2531602.2531650",
language = "English",
isbn = "9781450325400",
series = "Proceedings of the ACM Conference on Computer Supported Cooperative Work, CSCW",
publisher = "Association for Computing Machinery",
pages = "379--392",
booktitle = "CSCW 2014 - Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work and Social Computing",
note = "17th ACM Conference on Computer Supported Cooperative Work and Social Computing, CSCW 2014 ; Conference date: 15-02-2014 Through 19-02-2014",
}