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README.md

Twitter’s Glass Ceiling: The Effect of Perceived Gender on Online Visibility #######################

We obtained our dataset from Twitter gardenhose (10% sample of Twitter) in Feburary 2015. You can find the original tweet_ids in our dataset available here at: http://www.icwsm.org/2016/datasets/datasets/. The summary of our dataset including all the attributes used in our statistical analysis is published as summ_data.csv.

We used firstnames in 1900- 2013 U.S. Census documents to detect Twitter users' gender by their firstnames. We also used Face++ (http://www.faceplusplus.com/) to detect users' gender by their profile pictures.

The statistical analysis is done in R.

Please cite our paper using:

@inproceedings{nilizadeh-icwsm16, title = {Twitter's Glass Ceiling: The Effect of Perceived Gender on Online Visibility}, author = {Shirin Nilizadeh and Anne Groggel and Peter Lista and Srijita Das and Yong-Yeol Ahn and Apu Kapadia and Fabio Rojas}, booktitle = {Proceedings of The International AAAI Conference on Web and Social Media (ICWSM '16)}, month = may, year = {2016} }

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Twitter’s Glass Ceiling: The Effect of Perceived Gender on Online Visibility

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