Denna uppsats analyserar Cecilia Edefalks konstverk genom ett postmodernistiskt raster. Tre verk - En annan rörelse, In the Painting the Painting, Självporträtt - från 1990-talet undersöks avseende konstens utformning och påverkan av postmodernistiska konstuttryck. Genom diskursanalysens metod undersöks dessutom konstdebatten vid denna tidpunkt då postmodernismen vann terräng i Sverige samt hur konstkritiken yttrade sig avseende Edefalks konst. / This essay analyzes artworks by Cecilia Edefalk through a postmodernist lens. Three artworks - Another Movement, In the Painting the Painting, Selfportrait - from 1990s are examined regarding design and influence of postmodernist expressions. Through the method of discourse analysis the debate of art is investigated, as well as art critics regarding Edefalks artwork, at the time postmodernism developed in Sweden.

Software development is a collaborative process where many developers come together and work on a project. To make things easy and manageable, software is developed on a version control system. A version control system is a centralized system which stores code and adds code from all other developers as an increment to the code base in the repository. Since multiple people work on the same code repository together, it is important to make sure that their contributions do not conflict with each other. It is important to maintain the quality and integrity of the repository. This is where the code review process comes into the picture. All the changes made to the repository by developers are reviewed by other, preferably senior developers, before it is integrated into the repository. This is done to maintain a high standard of development. The problem is that this is a manual and highly time consuming process. This research proposes a tool that tries to optimize the code review process. This is done by ranking the changes that the developers need to review: this makes it easier for the developer to decide which change he/she needs to review first. Also since every reviewer has their own preference and style, the tool takes feedback from the code reviewer after every change and readjusts the ranked change list according to his/her feedback. Adding to that, the tool classifies each change and tags it so that the code reviewers have a better understanding of the change that he/she is about to review. It also provides additional refactoring information about each change. Refactoring changes are very easy to miss, since they are not usually erroneous changes, but they erode the quality of the software overtime. The tool points out these changes so that these changes are not missed by the code reviewer. The research was evaluated on 7 open source project and a usability study was conducted which prove that this tool does have a positive impact on the code review process.

Despite the widespread availability and importance of nonnumeric data, marketers do not have the tools to extract information from large amounts of nonnumeric data. This dissertation attempts to fill this void: I developed a scalable methodology that is capable of extracting information from extremely large volumes of nonnumeric data. The proposed methodology integrates concepts from information retrieval and content analysis to analyze textual information. This approach avoids a pervasive difficulty of traditional content analysis, namely the classification of terms into predetermined categories, by creating a linear composite of all terms in the document and, then, weighting the terms according to their inferred meaning. In the proposed approach, meaning is inferred by the collocation of the term across all the texts in the corpus. It is assumed that there is a lower dimensional space of concepts that underlies word usage. The semantics of each word are inferred by identifying its various contexts in a document and across documents (i.e., in the corpus). After the semantic similarity space is inferred from the corpus, the words in each document are weighted to obtain their representation on the lower dimensional semantic similarity space, effectively mapping the terms to the concept space and ultimately creating a score that measures the concept of interest. I propose an empirical application of the outlined methodology. For this empirical illustration, I revisit an important marketing problem, the effect of movie critics on the performance of the movies. In the extant literature, researchers have used an overall numerical rating of the review to capture the content of the movie reviews. I contend that valuable information present in the textual materials remains uncovered. I use the proposed methodology to extract this information from the nonnumeric text contained in a movie review. The proposed setting is particularly attractive to validate the methodology because the setting allows for a simple test of the text-derived metrics by comparing them to the numeric ratings provided by the reviewers. I empirically show the application of this methodology and traditional computer-aided content analytic methods to study an important marketing topic, the effect of movie critics on movie performance. In the empirical application of the proposed methodology, I use two datasets that combined contain more than 9,000 movie reviews nested in more than 250 movies. I am restudying this marketing problem in the light of directly obtaining information from the reviews instead of following the usual practice of using an overall rating or a classification of the review as either positive or negative. I find that the addition of direct content and structure of the review adds a significant amount of exploratory power as a determinant of movie performance, even in the presence of actual reviewer overall ratings (stars) and other controls. This effect is robust across distinct opertaionalizations of both the review content and the movie performance metrics. In fact, my findings suggest that as we move from sales to profitability to financial return measures, the role of the content of the review, and therefore the critic's role, becomes increasingly important.

No description available.

The purpose of this thesis is to find and categorize differences in the language used inonline reviews by early adopters. By filling this gap in knowledge, marketers can betterunderstand the nature of an online review, be it derived from professional or amateurearly adopters. These categorizations aim to pinpoint differences between professionalsand amateur reviewers who are considered to be early adopters of technology. Publiclyavailable third-party data was analysed using a descriptive text analysis tool, LIWC(Linguistic Inquiry and Word Count). The results regarding the professionals are highly conclusive seeing the uniformity of thepopulation. They compose long format, highly analytic, unpartisan reviews which canbe perceived as inauthentic due to the formality of the text and lack of personal opinions.With these traits, professional online reviews are subjected to the risk of alienating theiraudience, thus losing their influence over the potential adopters. The amateurs were not as uniform as the professionals. However, there are cleartendencies of shorter formats, personal experience-based writing which comes off as moreauthentic compared to the professionals. Within the population of amateurs, one canclearly distinguish that satisfied amateur reviewers’ write shorter reviews but morefrequently, compared to dissatisfied amateur reviewers who write longer format, but notas frequently. Due to the clear and statistically supported differences between the two populations, theyare easily distinguishable from each other. This also shows in their motives to post onlinereviews. Where professionals are financially incentivised, amateurs find their motivationin intrinsic motivators such as altruistic, egotistic, and other self-fulfilling motivators. These distinct differences enable marketers to allocate their efforts towards eitherprofessionals or amateur reviewers in order to achieve the desired market effect. To reacha customer on an emotional level, they should promote amateur reviews. But in order todisplay unadulterated facts and figures, they should promote professional reviews.

No description available.

No description available.