Meeting the challenge on the path to democracy: discursive strategies in governmental declarations

The communicative practice in the ex-GDR was complex and diverse, although public political discourse had been fairly ritualized. Text-types characteristic of the Communist Party discourse were full of general (superordinate) terms semantic specification was hardly possible (propositional reduction). Changes in the social world result in changes in the communicative practice as well. However, a systematic comparision of text-types across cultures and across ideological boundaries reveals both differences in the textual macro- and superstructures and overlapping as well as universal features, probably related to functional aspects (discourse of power). Six sample texts of the text-type `government declaration', two produced in the ex-GDR, four in the united Germany, are analysed. Special attention is paid to similarities and differences (i) in the textual superstructure (problem-solution schema), (ii) in the concepts that reflect the aims of political actions (simple worlds), (iii) in the agents who (are to) perform these actions (concrete vs abstract agents). Similarities are found mainly in the discursive strategies, e.g. legitimization text actions. Differences become obvious in the strategies used for legitimization, and also in the conceptual domains referred to by the problem-solution schema. The metaphors of construction, path and challenge are of particular interest in this respect.

Chronic illness in non-heterosexual contexts: towards a critical LGBTQ health psychology

In this thesis, I contribute to the expansion of lesbian, gay, bisexual, trans and queer (LGBTQ) psychology by examining chronic illness within non-heterosexual contexts. Chronic illness, beyond the confines of HIV/AIDS, has been a neglected topic in LGBTQ psychology and sexual identity is often overlooked within health psychology. When the health of lesbian, gay and bisexual (LGB) people has been considered there has been an over-reliance on quantitative methods and comparative approaches which seek to compare LGB people?s health to their heterosexual counterparts. In contrast, I adopt a critical perspective and qualitative methods to explore LGBTQ health. My research brings together ideas from LGBTQ psychology and critical health psychology to explore non-heterosexuals? experiences of chronic illness and the discursive contexts within which LGB people live with chronic health conditions. I also highlight the heteronormativity which pervades academic health psychology as well as the „lay? health literature. The research presented in this thesis draws on three different sources of qualitative data: a qualitative online questionnaire (n=190), an online discussion within a newsgroup for people with diabetes, and semi-structured interviews with 20 LGB people with diabetes. These data are analysed using critical realist forms of thematic analysis and discourse analysis. In the first analytic chapter (Chapter 3), I report the perspectives of LGB people living with many different chronic illnesses and how they felt their sexuality shapes their experiences of illness. In Chapter 4, I examine heterosexism within an online discussion and consider the ways in which sexuality is constructed as (ir)relevant to a diabetes support forum. In Chapter 5, I analyse LGB people?s talk about the support family and partners provide in relation to their diabetes and how they negotiate wider discourses of gender, sexuality and individualism. In Chapter 6 I explore how diabetes intersects with gay and bisexual men?s sex lives. In the concluding chapter, I discuss the contributions of my research for a critical LGBTQ health psychology and identify some possible areas for future research.

Taking the biscuit? A discursive approach to managing diet in type 2 diabetes

Adopting and maintaining a healthy diet is pivotal to diabetic regimens. Behavioural research has focused on strategies to modify/maintain healthy behaviours; thus 'compliance' and 'non-compliance' are operationalized by researchers. In contrast, discursive psychology focuses on the actions different accounts accomplish-in this case regarding diets. Using thematic discourse analysis, we examine dietary management talk in repeat-interviews with 40 newly diagnosed type 2 diabetes patients. Women in our study tended to construct dietary practices as an individual concern, while men presented food consumption as a family matter. Participants accounted for 'cheating' in complex ways that aim to accomplish, for instance, a compliant identity. Discursive psychology may facilitate fluidity in our understandings of dietary management, and challenge fixed notions of 'compliant' and 'non-compliant' diabetes patients. Copyright © 2005 SAGE Publications.

Group work and cognitive style:a discursive investigation

This article investigates the relationship between work-group members’ cognitive style (as measured by Allinson and Hayes’s Cognitive Style Index), the group’s task and setting, and the way in which group members behave in the group. Behavior of a homogeneous analytic, a homogeneous intuitive, and a heterogeneous group was observed in a mechanistic setting and analyzed using discourse analysis. This study is discussed in light of a previous study in which homogeneous analytic and homogeneous intuitive groups worked in an organic setting. These two studies use different methodologies (quantitative approach versus qualitativediscursive). The benefits of methodological eclecticism are discussed.

Multi-topic information filtering with a single user profile

In Information Filtering (IF) a user may be interested in several topics in parallel. But IF systems have been built on representational models derived from Information Retrieval and Text Categorization, which assume independence between terms. The linearity of these models results in user profiles that can only represent one topic of interest. We present a methodology that takes into account term dependencies to construct a single profile representation for multiple topics, in the form of a hierarchical term network. We also introduce a series of non-linear functions for evaluating documents against the profile. Initial experiments produced positive results.

Selling, resistance and reconciliation:a critical discursive approach to subsidiary role evolution in MNEs

Studies of political dynamics between multinational enterprise (MNE) parents and subsidiaries during subsidiary role evolution have focused largely on control and resistance. This paper adopts a critical discursive approach to enable an exploration of subtle dynamics in the way that both headquarters and subsidiaries subjectively reconstruct their independent-interdependent relationships with each other during change. We draw from a real-time qualitative study of a revealing case of charter change in an important European subsidiary of an MNE attempting to build closer integration across European country operations. Our results illustrate the role of three discourses – selling, resistance and reconciliation – in the reconstruction of the subsidiary–parent relationship. From this analysis we develop a process framework that elucidates the important role of these three discourses in the reconstruction of subsidiary roles, showing how resistance is not simply subversive but an important part of integration. Our findings contribute to a better understanding of the micro-level political dynamics in subsidiary role evolution, and of how voice is exercised in MNEs. This study also provides a rare example of discourse-based analysis in an MNE context, advancing our knowledge of how discursive methods can help to advance international business research more generally.

Articulating discursive and materialist conceptions of practice in the logics approach to critical policy analysis

In this article it is argued that while Glynos and Howarth’s logics of critical explanation (LCE) offers an important and promising contribution to critical policy analysis, it, along with other approaches that focus on the meaning of social action, faces a growing challenge in the form of a so-called new materialist turn in social and political theory. The article argues that there is much to be gained for the logics approach in paying closer attention to the materiality of practices in terms not only of lending greater clarity to the conception and role of social practices in the logics approach but also in enabling it fully to deliver on its critical ambition. The article explores an alternative materialist approach to the study of social practices, which hails from the post-actor–networktheory tradition and which has ontological affinities with post-structuralism. The article begins with a brief analysis of the new materialist turn in its various guises. It then critically examines the logics approach, and, in particular its conception of practice. It then explores an alternative materialist and ethnographic reading of practice, focusing on medical and care practices. It concludes with an examination of the implications for a more materialist conception of practices for the LCE’s broad deconstructive, psychoanalytic and onto-political ambitions.

Weakly supervised joint sentiment-topic detection from text

Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework called joint sentiment-topic (JST) model based on latent Dirichlet allocation (LDA), which detects sentiment and topic simultaneously from text. A reparameterized version of the JST model called Reverse-JST, obtained by reversing the sequence of sentiment and topic generation in the modeling process, is also studied. Although JST is equivalent to Reverse-JST without a hierarchical prior, extensive experiments show that when sentiment priors are added, JST performs consistently better than Reverse-JST. Besides, unlike supervised approaches to sentiment classification which often fail to produce satisfactory performance when shifting to other domains, the weakly supervised nature of JST makes it highly portable to other domains. This is verified by the experimental results on data sets from five different domains where the JST model even outperforms existing semi-supervised approaches in some of the data sets despite using no labeled documents. Moreover, the topics and topic sentiment detected by JST are indeed coherent and informative. We hypothesize that the JST model can readily meet the demand of large-scale sentiment analysis from the web in an open-ended fashion.

Feature LDA:a supervised topic model for automatic detection of web API documentations from the web

Web APIs have gained increasing popularity in recent Web service technology development owing to its simplicity of technology stack and the proliferation of mashups. However, efficiently discovering Web APIs and the relevant documentations on the Web is still a challenging task even with the best resources available on the Web. In this paper we cast the problem of detecting the Web API documentations as a text classification problem of classifying a given Web page as Web API associated or not. We propose a supervised generative topic model called feature latent Dirichlet allocation (feaLDA) which offers a generic probabilistic framework for automatic detection of Web APIs. feaLDA not only captures the correspondence between data and the associated class labels, but also provides a mechanism for incorporating side information such as labelled features automatically learned from data that can effectively help improving classification performance. Extensive experiments on our Web APIs documentation dataset shows that the feaLDA model outperforms three strong supervised baselines including naive Bayes, support vector machines, and the maximum entropy model, by over 3% in classification accuracy. In addition, feaLDA also gives superior performance when compared against other existing supervised topic models.

Topic continuity in informal conversations between native and non-native speakers of English

Topic management by non-native speakers (NNSs) during informal conversations has received comparatively little attention from researchers, and receives surprisingly little attention in second language learning and teaching. This article reports on one of the topic management strategies employed by international students during informal, social interactions with native-speaker peers, exploring the process of maintaining topic continuity following temporary suspensions of topics. The concept of side sequences is employed to illustrate the nature of different types of topic suspension, as well as the process of jointly negotiating a return to the topic. Extracts from the conversations show that such sequences were not exclusively occasioned by language difficulties, and that the non-native speaker participants were able to effect successful returns to the main topic of the conversations.

Collaborative futures:discursive realignments in austere times

This paper explores the future of collaboration in an era of austerity. Boundary object theory provides a framework to examine the significance and role of four key discourses in collaboration – efficiency, effectiveness, responsiveness and cultural performance. Crisis provides a way of examining how and in what ways discourses realign. The exploration of discourses aids critical analysis of collaboration across sectoral, geographical and disciplinary boundaries, highlighting the importance of understanding the contextual roots of collaboration theory and practice, and the implications of local/global dynamics.

Joint sentiment/topic model for sentiment analysis

Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework based on Latent Dirichlet Allocation (LDA), called joint sentiment/topic model (JST), which detects sentiment and topic simultaneously from text. Unlike other machine learning approaches to sentiment classification which often require labeled corpora for classifier training, the proposed JST model is fully unsupervised. The model has been evaluated on the movie review dataset to classify the review sentiment polarity and minimum prior information have also been explored to further improve the sentiment classification accuracy. Preliminary experiments have shown promising results achieved by JST.

Originator or propagator? Incorporating social role theory into topic models for twitter content analysis

A large number of studies have been devoted to modeling the contents and interactions between users on Twitter. In this paper, we propose a method inspired from Social Role Theory (SRT), which assumes that a user behaves differently in different roles in the generation process of Twitter content. We consider the two most distinctive social roles on Twitter: originator and propagator, who respectively posts original messages and retweets or forwards the messages from others. In addition, we also consider role-specific social interactions, especially implicit interactions between users who share some common interests. All the above elements are integrated into a novel regularized topic model. We evaluate the proposed method on real Twitter data. The results show that our method is more effective than the existing ones which do not distinguish social roles. Copyright 2013 ACM.