- Danescu-Niculescu-Mizil, C., Sudhof, M., Jurafsky, D., Leskovec, J., & Potts, C. (2013). A computational approach to politeness with application to social factors.
In this research a politeness classifier is constructed that performs with a good accuracy (near-human performance). Authors then use this classifier to explore the relation between politeness and social factors in three different categories namely: “relation to social outcome” (they show that later successful candidates are more polite than failed and non-admins), “politeness and power” (they depicts that requests posted by the question-asker are more polite than the other requests) and “prediction-based interactions” (some results like female Wikipedians are more polite).
Although building a politeness classifier seems very simple and it is similar to other text classifications (such as spam-ham classification), as it is mentioned in this paper, it can be useful for exploring politeness levels across several factors which can be an interesting research in social networks. Some applications of this classifier such as analyzing the relation between politeness and social status are mentioned in this paper, however, I am interested in using this classifier to predict the social status.
As in subsection 5.1 it is concluded, polite Wikipedia editors are more likely to reach high status through elections. I think some other features such as the number of edits that a candidate has done so far or even the candidate’s date of registration in the platform can also play significant roles in success of a candidate. But how is the significance level of the politeness factor on the success of the later successful candidates in the election? I am also curious to know if we can model Wikipedia admin elections (or other elections like this) with several features including politeness levels of the candidates. Can we use the classifier that introduced in this research to make a politeness score for each candidate and then employ it as a feature for prediction of Wikipedia administrator elections?
Also, in this research Amazon Mechanical Turk is used to label a portion of the data which come from the Wikipedia community of editors and the Stack Exchange question-answer community. They only employ annotators who are the U.S. residents (and also some other filtering). However, is this a good approach for labeling the request data? What about other countries’ residents? There are differences in politeness judgments between the two groups of users from two different cultures even with a same languages[1]. How can we use this labeling which is only based on the U.S residents judgment, in Wikipedia admin elections where many editors/users are active and using English language in there but are from other countries with different perceptions of politeness? This also makes me curious about another question. This kind of research are studying the politeness of users but what if we study the perceptions of politeness in social media?
I remember when I came to the U.S. had some difficulties in sending Email to professors or even other students. Although before coming to the U.S I had sent/received many Emails to/from professors, I realized that the politeness in this country is completely different only after I arrived here. In my country, we call each other by last name + Mrs/Ms/Miss/Mr in Emails. Using a lot of gratitude is also very common in our Emails. This way of writing Email sometimes even looks weird in the U.S., but for the people in my country the type of writing that is prevalent here seems impolite or even rude. In total, it seems a behavior study about the perceptions of politeness in social media can be useful. The results of this kind of research can prevent some misunderstandings and their consequences (such as some conflicts happen every day in social networks platforms).
[1] Yu-Cheng Lee, ‘Cultural Expectations and Perceptions of Politeness: The “Rude Chinese”?, DOI:10.5539/ass.v7n10p11
