Along with a team of Stanford University Sociologists led by Karen Cook and Paolo Parigi, I am conducting a study on behalf of Airbnb to understand the social consequences of sharing goods and services with strangers.
Karen has published multiple books on the formation of Trust in modern societies and more recently on the role of Trust in the online world. Paolo is also interested in social networks and has conducted previous studies of Trust in the sharing economy.
Together we will be surveying Airbnb members to better understand Trust inside and outside of the sharing economy, as well as what drives changes in Trust. Stay tuned for more!
Twitter‘s latest SEC filings declare that only 8.5% of their active accounts are probably robots. Thats 24 million of their 284 million active accounts. However, a previous report by the Wall Street Journal in April last year suggested that as many as 44% of twitter accounts have never tweeted.
The devil, as always, is in the detail. First of all in deciding what an ‘active’ account constitutes, and secondly in judging which criteria to use for classification as a ‘bot’ account.
Much of the task of a data scientist is precisely this problem of constructing sensible definitions, as well as understanding and communicating the implications of alternative definitions. A successful data scientist, like an academic researcher, will be able to accurately uncover the learnings from a dataset in different scenarios, and then action based on the likeliest scenario.