Paper #1: A computational approach to politeness with application to social factors
Paper #2: Language from police body camera footage shows racial disparities in officer respect
Summary #1:
This paper does a qualitative analysis of the linguistic features that relate to politeness. From there the authors create a machine learning model that can be used to automatically measure politeness. Authors use two different websites for testing the generalizability of the model. Based on the result the authors do quantitative analysis on the relationship between politeness and social outcome, the relationship between politeness and power. From the result, it appears that users who are more polite are more likely to be elected as admin and once elected they become less polite.
Summary #2:
This paper looks into police’s interaction with drivers seen from police body-camera which has been adopted recently due to controversy regarding their interaction with the black community. This paper introduces a computational model using only transcription of the speech between an officer and a driver. In the first part of the study, a group of 60 participants was used to rate utterances on two criteria, respect and formality. The study finds that there’s no significant difference in formality from police officers for both white and black community. In case of respect, this is significantly different. Based on these result the authors created a computation model to automatically predict score from the data.
Reflection #1:
This paper tried to infer the relationship between politeness and authority. Thier analysis is in some sense lacking. This becomes more evident from reading the paper 2 which does test for other factors that can affect any inference. For example, in this case, authors don’t check for the factors like the responsibility of admins, age difference etc. Although different levels of moderation capabilities are given to users with different reputation, it is common in StackOverflow for the admins to do a lot of moderation. If you look into the number of duplicate question it will be quite clear that to make the site useful to all types of users strict moderation is necessary for the questions from new users. Another factor that might have an affect on the politeness of the users is the age. It is common in StackOverflow that older users are ruder At the same time, they also have very high rating which correlates with thier chance of being a moderator. In the last election, I think one of the main question was about candidates attitude toward the strictness in moderation (Full disclosure: I have voted for Cody Gray in the last election). So these factors might have some effect on the analysis of politeness.
Reflection #2:
This study was done in an intuitive and simple manner. The authors created a model and tried to find out if it was affected by any control variables like severity of the offence, formality, outlier in data etc. The first thing that comes to mind from the method is that the model only focuses on the utterance in textual format rather than speech. It doesn’t appear to be a good ground truth as the RMSE of average users is about .842. The authors uses this partial ground truth from the rating of the human raters to build a computational model for predicting respectfulness in utterances. Another problem with the computational model is the transcribing part of the data is fully manual. In that perspective this is a semi-automatic model. A complex approach will be by using speech directly which solves the previous problem.
