Political participation as public pedagogy : The Educational Situation in Young People´s Political Conversations in Social Media

In this article we argue that young people’s political participation in the social media can be considered ‘public pedagogy’. The argument builds on a previous empirical analysis of a Swedish net community called Black Heart. Theoretically, the article is based on a particular notion of public pedagogy, education and Hannah Arendt’s expressive agonism. The political participation that takes place in the net community builds up an educational situation that involves central characteristics: communication, community building, a strong content focus and content production, argumentation and rule following. These characteristics pave the way for young people’s public voicing, experiencing, preferences and political interests that guide their everyday political life and learning – a phenomenon that we understand as a form of public pedagogy. 

Speak Good English Movement in Singapore : Reactions in Social and Traditional Media

The first Speak Good English Movement, SGEM, took place in 2000, and has been organized annually ever since. Speaking a “standard” form of English is considered to bring increased personal power. However, the SGEM wants the Singaporeans to use “standard” English in their private life as well. A decade after the beginning of the campaign, a Speak Good Singlish Movement was started. Based on studies of language and identity, it is understandable why some Singaporeans might feel the SGEM threatens their identity. However, the reactions towards the campaign are mainly positive. For the purposes of this analysis, Twitter messages, Facebook pages, and newspaper articles from The Straits Times were collected. The SGEM has hailed both direct and indirect praise and criticism in both social and traditional media: Five newspaper articles praise the campaign while five criticize it; the results are nine and seven respectively for social media. This thesis looks at reactions towards the SGEM in both social and traditional media, analyzes how these reactions might relate to the ideas of the power of language, its variety and the relation of language and identity.

How does data quality in a network affect heuristic solutions?

To have good data quality with high complexity is often seen to be important. Intuition says that the higher accuracy and complexity the data have the better the analytic solutions becomes if it is possible to handle the increasing computing time. However, for most of the practical computational problems, high complexity data means that computational times become too long or that heuristics used to solve the problem have difficulties to reach good solutions. This is even further stressed when the size of the combinatorial problem increases. Consequently, we often need a simplified data to deal with complex combinatorial problems. In this study we stress the question of how the complexity and accuracy in a network affect the quality of the heuristic solutions for different sizes of the combinatorial problem. We evaluate this question by applying the commonly used p-median model, which is used to find optimal locations in a network of p supply points that serve n demand points. To evaluate this, we vary both the accuracy (the number of nodes) of the network and the size of the combinatorial problem (p). The investigation is conducted by the means of a case study in a region in Sweden with an asymmetrically distributed population (15,000 weighted demand points), Dalecarlia. To locate 5 to 50 supply points we use the national transport administrations official road network (NVDB). The road network consists of 1.5 million nodes. To find the optimal location we start with 500 candidate nodes in the network and increase the number of candidate nodes in steps up to 67,000 (which is aggregated from the 1.5 million nodes). To find the optimal solution we use a simulated annealing algorithm with adaptive tuning of the temperature. The results show that there is a limited improvement in the optimal solutions when the accuracy in the road network increase and the combinatorial problem (low p) is simple. When the combinatorial problem is complex (large p) the improvements of increasing the accuracy in the road network are much larger. The results also show that choice of the best accuracy of the network depends on the complexity of the combinatorial (varying p) problem.