Aim: The aim for this study of Swedish daily press is to see how the musical reporting is structured for the newspapers I have chosen to analyse. My main purpose is to investigate how the newspapers reporting are distributed between artists who belong to either a major record company or an independent record company. With this research I want to find out if there are any economic backgrounds to the content and if the reporting is equal to the market production. Method/Material: For this study I have studied, by quantitative research, every piece of musical reporting in seven daily newspapers for two weeks. Through thorough research I have determined the belonging of every article’s record company. I have compared the newspapers with each other to see how the reporting differs. I have also collected information concerning the economic aspects of the music business to investigate if the reporting is equal to the market production. Main results: - The representation of major and independent record companies in Swedish press is distributed as the following: 60 % Major and 40 % Independent. - The national press and regional press both show a distorted picture of the record company representation while the evening press and free press show a more truthful representation according to the market share holdings. - There are signs of a scope economic structure in Bonnier which cannot be fully verified.

Finnish-born writer Susanna Alakoski’s novel Svinalängorna became a big success after being published in Sweden in April 2006. Though the novel has many themes in common with earlier literature written by and about Finnish immigrants in Sweden, little attention has been brought to this fact by reviewers and journalists. This essay examines connections between Alakoski’s novel and Finnish migrant literature in Sweden, mainly from the 1970s, and how these connections have been recognised by reviewers in Sweden and Finland. Based on the examination made here, Svinalängorna can be said to have several significant themes and features in common with other Finnish immigrant literature written in Sweden. However, in the examined material, none of the Swedish reviewers and only two of the Finnish reviewers referred to earlier literature written by and/or about Finns in Sweden. The main reference point for the Swedish reviewers was traditional Swedish working-class literature while the Finnish reviewers mainly referred to newer Finnish literature exploring similar themes: alcoholism, poverty and childhood. In general, the Finnish reviewers found the novel more familiar than the Swedish reviewers.

Previous research has shown how venting one’s feelings can reduce the negative emotions of a consumption experience. This study proposes a general process of how consumers with feelings of unfairness due to a negative consumption experience can achieve emotional disclosure and reduced unfairness by posting online reviews. By using an experimental design with scenarios, this study tests how the perceived unfairness in this process is affected by the party encouraging the consumer to post an online review and the consumer’s public commitment. A student sample was divided into four groups and the perception of unfairness was compared between the groups depending on whether the party encouraging the feedback was a company perceived to be responsible for the sense of unfairness or an independent party and whether when the consumer was identifiable or anonymous to see if public commitment had an effect. Results showed that emotional disclosure was found to reduce the perceived unfairness in all groups. There was no significant difference between being encouraged by the company or independent party. Furthermore, no public commitment was in effect, even when participants’ answers were thought to become known to others. The results indicate that companies may prefer to encourage consumers to provide feedback themselves rather than using a third party and that posting online reviews will not make the consumer committed to their feeling of unfairness.

Consumer-generated reviews play an important role in online purchase decisions for many consumers. However, the quality and helpfulness of online reviews varies significantly. In addition, the helpfulness of different consumer-generated reviews is not disclosed to consumers unless they carefully analyze the overwhelming number of available contents. Therefore, it is of vital importance to develop predictive models that can evaluate online product reviews efficiently and then display the most useful reviews to consumers, in order to assist them in making purchase decisions. This thesis examines the problem of building computational models for predicting whether a consumer-generated review is helpful based on consumers' online votes on other reviews (where a consumer's vote on a review is either HELPFUL or UNHELPFUL), with the aim of suggesting the most suitable products and vendors to consumers.In particular, we propose in this thesis three different helpfulness prediction approaches for consumer-generated reviews. Our entropy-based approach is relatively simple and suitable for applications requiring simple recommendation engine with fully-voted reviews. However, our entropy-based approach, as well as the existing approaches, lack a general framework and are all limited to utilizing fully-voted reviews. We therefore present a probabilistic helpfulness prediction framework to overcome these limitations. To demonstrate the versatility and flexibility of this framework, we propose an EM-based model and a logistic regression-based model. We show that the EM-based model can utilize reviews voted by a very small number of voters as the training set, and the logistic regression-based model is suitable for real-time helpfulness predicting of consumer-generated reviews. To our best knowledge, this is the first framework for modeling review helpfulness and measuring the goodness of models. Although this thesis primarily considers the problem of review helpfulness prediction, the presented probabilistic methodologies are, in general, applicable for developing recommender systems that make recommendation based on other forms of user-generated contents.

This thesis will discuss the emerging influence of film review aggregators and their effect on the changing landscape for reviews in the film industry. Specifically, this study will look at the top 150 domestic grossing films of 2010 to empirically study the effects of two specific review aggregators. A time-delayed approach to regression analysis is used to measure the influencing effects of these aggregators in the long run. Subsequently, other factors crucial to predicting film success are also analyzed in the context of sustained earnings.

Consumer-generated reviews play an important role in online purchase decisions for many consumers. However, the quality and helpfulness of online reviews varies significantly. In addition, the helpfulness of different consumer-generated reviews is not disclosed to consumers unless they carefully analyze the overwhelming number of available contents. Therefore, it is of vital importance to develop predictive models that can evaluate online product reviews efficiently and then display the most useful reviews to consumers, in order to assist them in making purchase decisions. This thesis examines the problem of building computational models for predicting whether a consumer-generated review is helpful based on consumers' online votes on other reviews (where a consumer's vote on a review is either HELPFUL or UNHELPFUL), with the aim of suggesting the most suitable products and vendors to consumers.In particular, we propose in this thesis three different helpfulness prediction approaches for consumer-generated reviews. Our entropy-based approach is relatively simple and suitable for applications requiring simple recommendation engine with fully-voted reviews. However, our entropy-based approach, as well as the existing approaches, lack a general framework and are all limited to utilizing fully-voted reviews. We therefore present a probabilistic helpfulness prediction framework to overcome these limitations. To demonstrate the versatility and flexibility of this framework, we propose an EM-based model and a logistic regression-based model. We show that the EM-based model can utilize reviews voted by a very small number of voters as the training set, and the logistic regression-based model is suitable for real-time helpfulness predicting of consumer-generated reviews. To our best knowledge, this is the first framework for modeling review helpfulness and measuring the goodness of models. Although this thesis primarily considers the problem of review helpfulness prediction, the presented probabilistic methodologies are, in general, applicable for developing recommender systems that make recommendation based on other forms of user-generated contents.

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Abstract Introduction Word-of-mouth (WOM) is based on personal recommendations where the sender is known by the consumer, thus, the persuasive nature of WOM is attributed to trust between the sender and the receiver of a message. Electronic word-of-mouth (eWOM) however, eliminates the consumer’s ability to judge the credibility of sender and message. Nevertheless, a high amount of people read online reviews about products and therefore make use of eWOM. Online reviews can be anonymous or can offer additional personal details of the sender and can have an influence on the credibility of the message, which in turn, can induce different attitudes towards specific products. Purpose This study aims to identify as well as understand the relationship between anonymous and semi anonymous eWOM and its corresponding characteristics in regards to the attitudes of consumers towards a laptop computer. Methodology A qualitative research method was conducted with the intention to understand the relationship between anonymous and semi anonymous eWOM towards consumers attitude. Primary data was collected, as the authors of this study were not able to locate research studies concerning the difference between anonymous and semi-anonymous eWOM and its relationship towards consumer’s attitudes. For this reason, four focus groups were carried out with students from the Jönköping University. During a pilot study, differences between male and female participants became visible therefore the focus groups were separated between men and women with the intention of collecting significant data. Conclusion The research was successful as it led to identify a relationship between the personal attributes of an online reviewer and the consumer attitudes towards a laptop. By reading online reviews and thus, observing the opinion of other people as well as using comparisons of different laptops, consumers form attitudes towards laptops. Moreover, it appears that consumers’ attitudes are more likely to be influenced by the message if it is perceived as credible. Several personal attributes of a reviewer such as name, photograph of a person, pseudonym, age, gender, country of residence and profession were identified to have an influence on the credibility of a message, whether they might increase or decrease the credibility. Additionally, it became visible, that women are relatively more likely to be influenced by personal attributes of a reviewer than men.

The purpose of this study is to identify the representations and stereotypes that are used in reviews to describe male and female pop artists and further on argue the consequenses these theses bring to the construction of male and female performers in society. The main question is: In what way do live act reviews present male and female pop artists?   A qualitative content analysis with tools from rhetoric analysis was used to answer this question. The content of Swedish newspapers Aftonbladet and Svenska Dagbladet was chosen to represent the media. The study is based on social constructionism and focuses on gender and stereotypes. These theories claim that men create the patterns that rule society and that women are unknowingly accepting this. We slowly grow into these stereotypical patterns so that we hardly recognize them anymore. The main reason for this is that the media provides information that is said to be objective, when it’s really influenced by the norms of society itself.   The result of the study proves that female artists are being held back by the unwritten rules of society while male artists are encouraged when it comes to developing themselves and their artwork. Women artists are portrayed as sexual and the journalists focus on details such as flaws regarding their singing skills. Male artists are portrayed in a more positive way and are mainly described as good entertainers.

The aim of this essay is to examine the differences in language use between the genders in game reviews, to find whether there are differences in the use of the language depending on gender. Both sexist language and technical aspects are examined, the technical aspects of writing have been chosen from previous research about gendered differences in writing. The reviews are randomly chosen but the games are selected. There is an equal amount of games with male and female main characters, and the number of reviews is chosen according to the number of reviews written by females, as there are fewer of them, and thus easier to find a matching number of reviews written by males rather than vice versa. The reviews are then examined to find sexist language and differences. This essay finds that there is sexist language in the writing of both genders, such as marked language, but only when the main character of the game is female. Both genders tend to focus on the appearance of female characters and the characteristics of male characters, but there is no known previous research about male and female game characters to compare these results to. However, the technical differences remain consistent with previous research on the same subject, such as female reviewers using more pronouns than male reviewers, and male reviewers using fewer verbs than female reviewers.