Comparing Social Work Students' Perceptions of Risk Using Online Discussion Fora: Lessons Learned from a European Pilot Project

Comparisons of international child welfare systems have identified two basic orientations to practice; a ‘child protection’ orientation and a ‘child welfare’ orientation, which are founded upon fundamentally different values and assumptions regarding the family, the origins of child care problems, and the proper role of the state in relation to the family. This paper describes a project which sought to compare how undergraduate social work students from three European Universities perceive risk in referrals about the welfare of children and to explore the impact of different cultural, ideological and educational contexts on the way in which risk is constructed by students. Students from Northern Ireland, Germany and Poland examined three vignettes via ten online discussion fora each of which provided a narrative summary of their discussion. The paper presents some findings from the analysis of the qualitative data emerging from the student discussions and draws out the lessons learned in terms of how the project was designed and implemented using online discussion fora.

Unsupervised Solution Post Identification from Discussion Forums

Discussion forums have evolved into a dependablesource of knowledge to solvecommon problems. However, only a minorityof the posts in discussion forumsare solution posts. Identifying solutionposts from discussion forums, hence, is animportant research problem. In this paper,we present a technique for unsupervisedsolution post identification leveraginga so far unexplored textual feature, thatof lexical correlations between problemsand solutions. We use translation modelsand language models to exploit lexicalcorrelations and solution post characterrespectively. Our technique is designedto not rely much on structural featuressuch as post metadata since suchfeatures are often not uniformly availableacross forums. Our clustering-based iterativesolution identification approach basedon the EM-formulation performs favorablyin an empirical evaluation, beatingthe only unsupervised solution identificationtechnique from literature by a verylarge margin. We also show that our unsupervisedtechnique is competitive againstmethods that require supervision, outperformingone such technique comfortably.

Retrieving Similar Discussion Forum Threads: A Structure based Approach

Online forums are becoming a popular way of finding useful
information on the web. Search over forums for existing discussion
threads so far is limited to keyword-based search due
to the minimal effort required on part of the users. However,
it is often not possible to capture all the relevant context in a
complex query using a small number of keywords. Examplebased
search that retrieves similar discussion threads given
one exemplary thread is an alternate approach that can help
the user provide richer context and vastly improve forum
search results. In this paper, we address the problem of
finding similar threads to a given thread. Towards this, we
propose a novel methodology to estimate similarity between
discussion threads. Our method exploits the thread structure
to decompose threads in to set of weighted overlapping
components. It then estimates pairwise thread similarities
by quantifying how well the information in the threads are
mutually contained within each other using lexical similarities
between their underlying components. We compare our
proposed methods on real datasets against state-of-the-art
thread retrieval mechanisms wherein we illustrate that our
techniques outperform others by large margins on popular
retrieval evaluation measures such as NDCG, MAP, Precision@k
and MRR. In particular, consistent improvements of
up to 10% are observed on all evaluation measures

A standing ovation for Nigel: An informal study

This article analyses a series of emails thanking Nigel for his stewardship of JASSS and the characteristics of their authors. It identifies a correlation between two measures of author activity in social simulation research, but no pattern between these activity measures and the email timing. Instead, the sequence suggests a classic standing ovation effect.