Predicting discussions on the social semantic web

Social Web platforms are quickly becoming the natural place for people to engage in discussing current events, topics, and policies. Analysing such discussions is of high value to analysts who are interested in assessing up-to-the-minute public opinion, consensus, and trends. However, we have a limited understanding of how content and user features can influence the amount of response that posts (e.g., Twitter messages) receive, and how this can impact the growth of discussion threads. Understanding these dynamics can help users to issue better posts, and enable analysts to make timely predictions on which discussion threads will evolve into active ones and which are likely to wither too quickly. In this paper we present an approach for predicting discussions on the Social Web, by (a) identifying seed posts, then (b) making predictions on the level of discussion that such posts will generate. We explore the use of post-content and user features and their subsequent e!ects on predictions. Our experiments produced an optimum F1 score of 0.848 for identifying seed posts, and an average measure of 0.673 for Normalised Discounted Cumulative Gain when predicting discussion levels

Question Asking During Reading Comprehension Instruction:A Corpus Study of How Question Type Influences the Linguistic Complexity of Primary School Students’ Responses

The authors examined teachers’ (N = 19) use of different question types during small‐group comprehension instruction for 6–11‐year‐olds (N = 115). The authors tagged the corpus of 40 hours of guided reading sessions to enable computer‐based searches for syntactic forms of questions. Teachers frequently asked high‐challenge wh‐ word questions (e.g., “How does that fit in with what you just read?”), and this was more pronounced in schools located in regions of low socioeconomic status, a finding associated with recency of completion of teacher training. Students’ responses were more linguistically complex when teacher questions comprised a high frequency of high‐challenge questions, particularly wh‐ word adverb questions (predominantly why and how). These findings applied across the wide age and ability range of the sample, indicating that high‐challenge questions are effective in small‐group comprehension instruction for students in different age groups and at various levels of reading ability. The authors conclude that teachers benefit from being informed about the effect of various syntactic forms of questions, particularly the nuances of wh‐ word questions. The findings also highlight the advantages of using corpus search methods to examine the influence of teacher question‐asking strategies during classroom interactions