This study seeks to investigate this core research topic: how identity is involved in everyday interactions between Chinese microblogging website users? By understanding identity as an element in the interaction context of discursive practices, the investigation is achieved through the analysis of naturally occurring text-based online data. Conversation Analysis (CA) and Membership Categorization Analysis (MCA) are used to do the analysis. The former will focus on the interaction structure while the latter will be used to make some of the contents in the interactions relevant. This study seeks to make the “orderliness” (Sacks, 1972) and “members’ methods” (Garfinkel, 1967) under a particular context describable and analyzable. The sequential and categorical organization described in this study shows how members are oriented to identities in the in situ context when they exchange their ideas on a sensitive topic, and on a microblogging website. / text

published_or_final_version / English / Doctoral / Doctor of Philosophy

No description available.

Firms are believed to engage in strategic political management (SPM) in attempts to shape public policy in favorable ways and enhance their economic returns. Extant research has broadly considered the motivations leading to corporate political activity, focusing on the effects of market power using metrics such as firm size and industry concentration to investigate this phenomenon. More recently, scholars have proposed a more nuanced perspective on the subject, suggesting that different types of SPM may exist. For example, both Baysinger (1984) and Oliver and Holzinger (2008) have distinguished between corporate political strategies designed to maintain or alter the firm’s political environment. In this study, I seek to more critically explore this distinction. I propose that at least two different types of SPM exist: defensive SPM, which is directed at protecting existing competitive advantage, and offensive SPM, which is focused on creating new forms of competitive advantage. I further propose that the threats and opportunities in a firm’s regulatory environment are important motivators of these different types of SPM. In the context of the natural gas industry in Texas from 1999-2009, I find that the degree of regulatory uncertainty in the firm’s political environment influences it to engage in defensive SPM. I also find that the size of the firm’s asset inventory influences it to engage in offensive SPM. Furthermore, I find that regulatory uncertainty negatively moderates the relationship between the size of a firm’s asset inventory and its likelihood of investing in offensive SPM. / text

The present study proposes a significant role for host country nationals (HCNs) in the expatriate adjustment process. Based on self-categorizaton theory, newcomer socialization research, organizational citizenship behavior (OCB) research, and models of expatriate adjustment, I present a model proposing how social categorization processes influence HCNs' willingness to engage in adjustment-facilitating organizational citizenship behaviors (AOCBs). I further propose that these behaviors have a significant impact on expatriates' adjustment and in turn, other important job-related outcomes of the expatriate. Hypotheses were tested on 115 expatriates and 53 HCNs. Expatriates were contacted directly or via an organizational contact. HCNs were either contacted directly or nominated by their expatriate counterpart to participate in the study. Results reveal support for the main tenets of the model. The willingness to engage in AOCBs was related to outgroup categorization, collectivism, and perceptions of justice. Social support provided by HCNs was found to significantly relate to HCNs' perceptions of their expatriate co-worker's adjustment. Expatriates, however, indicated that spousal adjustment and language ability were more important for their own adjustment. Adjustment was related to other key expatriate outcomes. The research and managerial implications of these results are discussed.

The current study investigated the developmental course of how young children label various facial expressions of emotion. 160 children (2 to 5 years) freely produced labels for six prototypical facial expressions of emotion and six animals. Even 2-year-olds were able to correctly label 5 of 6 animals, but the proportion of correct specific emotion category responses for this age group was < .30 for each of the six facial expressions. The 5-year-olds' proportion of correct specific emotion category labels was at ceiling for the happy and angry faces, but significantly lower for each of the other four facial expressions, and at floor level for the disgust face. The type of errors in labeling facial expressions changed with age: when incorrect, the youngest children produced any emotion label; older children produced labels of the correct valence; and the majority of the 5-year-olds' responses were of the correct specific emotion category. These results indicate that the free-labeling task per se is not too difficult even for 2-year-olds, but that children's use of emotion terms is not initially linked to facial expressions. Thus, the children's production of emotion terms far exceeded their proportion of correct specific emotion category labels. With age, children's implicit definition of emotion terms develops to include the associated facial expression, though this process is not complete for all expressions before the age of 6 years.

Identifying the language used will typically be the first step in most natural language processing tasks. Among the wide variety of language identification methods discussed in the literature, the ones employing the Cavnar and Trenkle (1994) approach to text categorization based on character n-gram frequencies have been particularly successful. This paper presents the R extension package textcat for n-gram based text categorization which implements both the Cavnar and Trenkle approach as well as a reduced n-gram approach designed to remove redundancies of the original approach. A multi-lingual corpus obtained from the Wikipedia pages available on a selection of topics is used to illustrate the functionality of the package and the performance of the provided language identification methods. (authors' abstract)

The theme of Master project is a posibility to use arificial neural networks for textual analysis and automatic categorization of textual documents in editorial programs. The task of the work was to analyze diferent methods of text clasification using diferent neural networks (SOM, Feed Forward, Learning Vector Quantization, etc.). There are much researchers who works on text clasification and artificial neural networks, but there is no practical fitting of such research. In this work I tried to find posibilities and dificulties of practical use of text clasification. I find that very important thing is initial amount and quality of information and not all neural networks fits for solving text categorization problems.

In our environment we do two things with objects: identify them, and act on them. Perhaps not coincidentally, research has shown that the brain appears to have two distinct visual streams, one that is engaged during the identification of objects, and one that is associated with action. Although these visual streams are distinct, there has been increasing interest in how the action and identification systems interact during grasping and identification tasks. In particular, the current research explored the role that previous motor experience with familiar manipulable objects might have on the time it takes healthy participants to identify these objects (relative to non-manipulable objects). Furthermore, previous research has shown that there are multiple, computationally and neuro-anatomically different, action systems. The current research was particularly interested in the action systems involved in 1) grasping, and 2) functionally using an object. Work began by developed a new stimulus set of black & white photographs of manipulable and non-manipulable objects, and collecting ‘graspability’ and ‘functional usage’ ratings (chapter 2). This stimulus set was then used to show that high manipulability was related to faster naming but slower categorization (chapter 3). In chapter 4, the nature of these effects was explored by extending a computational model by Yoon, Heinke and Humphreys (2002). Results from chapter 5 indicated independent roles of graspability and functional usage during tasks that required identification of objects presented either with or without a concurrent mask. Specifically, graspaility effects were larger for items that were not masked; and functional use effects were larger for items that were masked. Finally, chapter 6 indicated that action effects during identification tasks are partly based on how realistic the depictions of the objects are. That is, results from chapter 6 indicated the manipulability effects are larger for photographs than they are for line-drawings of the same objects. These results have direct implications for the design of future identification tasks, but, more broadly, they speak to the interactive nature of the human mind: Action representations can be invoked and measured during simple identification tasks, even where acting on the object is not required. / Manuscript-based dissertation. One introductory chapter, one concluding chapter, and five manuscripts (seven chapters in total).

What makes us like or dislike certain games? Is there relation between our tastes in games and our personalities and can it be measured? This dissertation examines gamer personalities and game attributes with the help of the Five-Factor Model, also called The Big Five. It treats an experiment on how to apply the Five-Factor Model to games and their players and what it may be used for. By interviewing gamers, recording their favored and unfavored games, letting the gamers take a Big Five personality test and then juxtapose their personalities with their games' attributes, those questions may be answered.