Hiroko Otsuka

An exploratory study for analyzing interactional processes of group discussion: the case of a focus group interview

The purposes of this study are (a) to establish a measurement for evaluating conversational impressions of group discussions, and (b) to make an exploratory investigation on their interactional processes which may affect to form those impressions. The impression rating and factor analysis undertaken first give us four factors concerning conversational impressions of “focus group interviews (FGIs)”: conversational activeness, conversational sequencing, the attitudes of participants and the relationships of participants. In relation to the factors of conversational activeness and conversational sequencing in particular, the microanalysis of four selected topical scenes from our database further shows that the behavior of the moderator and the interviewees is organized not independently but with reference to each other. The study thus emphasizes the importance of the integration of quantitative and qualitative approaches towards human interactions.

Identifying Tweets that Contain a źHeartwarming Storyź

We present a rather new task of detecting and collecting tweets that contain heartwarming stories from a huge amount of tweets on Twitter in this paper. We also present a method for identifying heartwarming tweets. Our prediction method is based on a supervised learning algorithm in SVM along with features from the tweets. We found by comparing the feature sets that adding sentiment features mostly improves the performance. However, simply adding the features for detecting a story in a tweet (past tense and tweet length) cannot contribute to improving the performance, while adding all the features to the baseline feature set mostly yields the best performance from among the feature sets.