How to Analyze Communication Data from Laboratory Experiments Without Being a Machine Learning Specialist
نویسندگان
چکیده
Recently, the analysis of communication has gained attention in experimental research. One important question is whether certain types affect decisions differently than others. In this regard, Houser & Xiao (2011) present an approach for classification natural language messages. The primary limitation their its limited applicability to large message datasets. Therefore, Penczynski (2019) extends methodological instruments by applying a machine learning classifier data. This accompanied problem dearth knowledge among experimenters. Hence, paper presents that employs publicly available text application. makes it possible analyze larger datasets based on small training classified beforehand human evaluators. As first step, I use data reported Charness and Dufwenberg (2006) generate both test Following approach, am able substantially replicate original results obtained Dufwenberg. second step again involves messages from as data, while take related trust game published Deck et al. (2013) test, dataset. Promisingly, also external evaluators, findings suggest can be used datasets, if artificial intelligence trained with very same experiment comparable experiment.
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ژورنال
عنوان ژورنال: Journal of Economics and Behavioral Studies
سال: 2021
ISSN: ['2220-6140']
DOI: https://doi.org/10.22610/jebs.v13i1(j).3083