APA
Click to copy
Mertens, A., Pradel, F., Rozyjumayeva, A., & Wäckerle, J. (2019). As the Tweet, so the Reply? Gender Bias in Digital Communication with Politicians. In Proceedings of the 10th ACM Conference on Web Science (pp. 193–201). Boston, Massachusetts, USA.
Chicago/Turabian
Click to copy
Mertens, Armin, Franziska Pradel, Ayjeren Rozyjumayeva, and Jens Wäckerle. “As the Tweet, so the Reply? Gender Bias in Digital Communication with Politicians.” In Proceedings of the 10th ACM Conference on Web Science, 193–201. Boston, Massachusetts, USA, 2019.
MLA
Click to copy
Mertens, Armin, et al. “As the Tweet, so the Reply? Gender Bias in Digital Communication with Politicians.” Proceedings of the 10th ACM Conference on Web Science, 2019, pp. 193–201.
BibTeX Click to copy
@inproceedings{armin2019a,
title = {As the Tweet, so the Reply? Gender Bias in Digital Communication with Politicians},
year = {2019},
address = {Boston, Massachusetts, USA},
pages = {193–201},
author = {Mertens, Armin and Pradel, Franziska and Rozyjumayeva, Ayjeren and Wäckerle, Jens},
booktitle = {Proceedings of the 10th ACM Conference on Web Science}
}
This study investigates gender bias in political interactions on digital platforms by considering how politicians present themselves on Twitter and how they are approached by others. Incorporating social identity theory, we use dictionary analyses to detect biases in individual tweets connected to the German federal elections in 2017. Besides sentiment analysis, we introduce a new measure of personal- vs. job-related content in text data, that is validated with structural topic models. Our results indicate that politicians' communication on Twitter is driven by party identity rather than gender. However, we find systematic gender differences in tweets directed at politicians: female politicians are significantly more likely to be reduced to their gender rather than to their profession compared to male politicians.
