In 2006 UPM was able to gain a level of social legitimacy that allowed it to carry out one of the largest industrial restructuring programmes in Finnish industrial history, shut down major operations in Finland and still appear to be functioning in the interests of the nation as well as itself. This study considers and examines various contexts of this shutdown with the aim of demonstrating how profoundly mediated such organizational events are though they appear to be produced primarily through strategic company decisions. The study aims to examine the processes of mediation at two levels. At one level, through close analysis of press releases and newspaper reports in local and national newspapers, the study presents a discursive analysis of the Voikkaa case. The discursive analysis focuses on providing historical contexts for understanding why this organizational event was also an occasion for reimagining the past and future of the Finnish nation; spatial contexts for understanding the differing struggles over the meaning of the event nationally and regionally; and the temporal dynamics of the media reports. At another level, the study considers and refines methods for reading and analyzing mediation in organization studies. Bringing together recent research of media text–based legitimation studies, emerging research on organizational memory and organizational death and a Foucaultian analytics of power, this work suggests that organizational research needs to be less concerned with particular typologies and narratives of shutdowns, and more curious about the processes of mediation through which organizational events are imagined and remembered.
In this thesis we study the field of opinion mining by giving a comprehensive review of the available research that has been done in this topic. Also using this available knowledge we present a case study of a multilevel opinion mining system for a student organization's sales management system. We describe the field of opinion mining by discussing its historical roots, its motivations and applications as well as the different scientific approaches that have been used to solve this challenging problem of mining opinions. To deal with this huge subfield of natural language processing, we first give an abstraction of the problem of opinion mining and describe the theoretical frameworks that are available for dealing with appraisal language. Then we discuss the relation between opinion mining and computational linguistics which is a crucial pre-processing step for the accuracy of the subsequent steps of opinion mining. The second part of our thesis deals with the semantics of opinions where we describe the different ways used to collect lists of opinion words as well as the methods and techniques available for extracting knowledge from opinions present in unstructured textual data. In the part about collecting lists of opinion words we describe manual, semi manual and automatic ways to do so and give a review of the available lists that are used as gold standards in opinion mining research. For the methods and techniques of opinion mining we divide the task into three levels that are the document, sentence and feature level. The techniques that are presented in the document and sentence level are divided into supervised and unsupervised approaches that are used to determine the subjectivity and polarity of texts and sentences at these levels of analysis. At the feature level we give a description of the techniques available for finding the opinion targets, the polarity of the opinions about these opinion targets and the opinion holders. Also at the feature level we discuss the various ways to summarize and visualize the results of this level of analysis. In the third part of our thesis we present a case study of a sales management system that uses free form text and that can benefit from an opinion mining system. Using the knowledge gathered in the review of this field we provide a theoretical multi level opinion mining system (MLOM) that can perform most of the tasks needed from an opinion mining system. Based on the previous research we give some hints that many of the laborious market research tasks that are done by the sales force, which uses this sales management system, can improve their insight about their partners and by that increase the quality of their sales services and their overall results.