@inproceedings{22386df8c2db473ba87750f54ff3e5ed,
title = "{"}twitter archeology{"} of learning analytics and knowledge conferences",
abstract = "The goal of the present study was to uncover new insights about the learning analytics community by analyzing Twitter archives from the past four Learning Analytics and Knowledge (LAK) conferences. Through descriptive analysis, in- teraction network analysis, hashtag analysis, and topic modeling, we found: extended coverage of the community over the years; increasing interactions among its members regard- less of peripheral and in-persistent participation; increasingly dense, connected and balanced social networks; and more and more diverse research topics. Detailed inspection of semantic topics uncovered insights complementary to the analysis of LAK publications in previous research.",
keywords = "Hashtag Analysis, Learning Analytics, Social Net-work, Topic Modeling, Twitter, Twitter Analytics",
author = "Bodong Chen and Xin Chen and Wanli Xing",
year = "2015",
month = mar,
day = "16",
doi = "10.1145/2723576.2723584",
language = "English (US)",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
pages = "340--349",
booktitle = "Proceedings of the 5th International Conference on Learning Analytics and Knowledge, LAK 2015",
note = "5th International Conference on Learning Analytics and Knowledge, LAK 2015 ; Conference date: 16-03-2015 Through 20-03-2015",
}