This study explores the use of Natural Language Processing as a tool for online reviews. By drawing on theories about machine learning, this article investigates how to develop a Natural Language Processing model in Python. The authors present two machine learning models which were developed through an iterative design process and by implementing various approaches from the TRIN-model. This study concludes that machine learning models like ours might not have a significant impact on the future of reviews, but we are optimistic about the potential of Natural Language Processing as a tool for categorizing specific aspects of a company’s services. This conclusion is based on the analysis and discussion of the results we gathered from our Natural Language Processing models.
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This project examines the influence of the myth of Danish design on the consumption of Danish furniture. Danish design has historically been associated with qualities such as timelessness, craftsmanship, tradition and beauty and has played a significant role in the development of Danish society and culture. The construction of the category of modernist Danish design and its narratives was shaped by a social network of individuals and organizations, linking Danish design to notions of good taste and healthy living. Today, Danish design is praised for the same understated and high-quality features which legitimize its contemporary success.By drawing on Roland Barthes' theory of myth and Pierre Bourdieu's concept of cultural capital, this study investigates both the way in which the myth of Danish design is created, and consumed. The analysis combines a semiotic examination of Danish design mythology with a conceptual content analysis of interviews conducted by a Danish furniture company, Fredericia, as part of their celebration of Børge Mogensen's Folkestolen’s 75th anniversary.The findings reveal that the myth of Danish design influences the consumption of Danish furniture by communicating symbolic valuations associated with positive attributes such as beauty, timelessness, and fine craftsmanship. Simultaneously, the myth perpetuates ideological narratives that serve the interests of dominant power groups in society, including the Danish nation state, the furniture industry and even certain groups of consumers. The furniture industry strategically exploits the myth to drive desirability and capitalize on the associations carried within Danish design.This research underscores the sociocultural function of myth, which constructs markers of social, national, and personal identity. Danish furniture transcends its functional and aesthetic aspects, becoming a symbol of economic and cultural wealth and social status. Simultaneously, the myth of Danish design distorts ideological narratives around class dominance and power and naturalizes the notions of nationalism and Danishness into signifieds of tradition, health, functionalism, sustainability, and social accessibility. The analysis situates consumption within the context of cultural capital, modern mythology, and late-stage capitalism, highlighting the transformation of furniture into tools for managing self-identity, and signifiers of social status and taste. The holders of cultural capital benefit from perpetuating the myth of Danish design, securing both material and symbolic profits from ownership of Danish furniture. Thus the class elite utilizes its cultural competence to maintain its capital and power dominance in society, as cultural capital reproduces social structures.This research investigates the complex interplay between the myth of Danish design, the consumption of Danish furniture, and their sociocultural implications. By critically examining the myth's influence, this study offers insights into the mechanisms by which design narratives and cultural capital shape consumption and perpetuate power dynamics in society.
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This report illustrates the factors that influence the decision-making processes of individuals whentaking part in the contemporary art market, notwithstanding the risk often attributed to such asset and the economic uncertainty of periods such as the aftermath of Covid-19. By examining the motivations from different perspectives, this report aims to shed light on the dynamics of the contemporary art market and its resilience in the face of economic instability. To answer the research question what factors drive individuals in Denmark to take part in the contemporary art market amidst the current economic uncertainty? We carry out semi-structured interviews with two amateur art buyers, one curator, and two owners of renowned contemporary art galleries. The results show that investing in contemporary art 1) yields socio-economic advantages 2) is influenced by trust towards the artist, and 3) is a matter of familial background. The research emphasizes how these factors influences the perception of risk in the individuals when investing in a piece of contemporary art. The purpose of this study is to identify the key factors that affect participants' engagement with the art market by investigating their personal motivations, risk perceptions, and investment strategies. The research is also particularly useful and relevant given the current economic uncertainty and its potential effects on the investment landscape. The results of this study will add to the body of knowledge that exists aboutthe contemporary art investment market by giving a more in-depth and precise understanding of the factors that influence people to invest in art despite the current state of the economy.
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This paper, seeks to examine the correlation between stock price and public sentiment expressed through social media. Through twitter scraping and pre- processing, sentiment can be extracted from text. The paper will be based on a heuristic approach to natural language processing. Furthermore, the paper will rely on the most common forms of sentiment analysis, using a rule-based and a machine-learning approach as a starting point and weigh these up against each other. Finally, we will continue with the best performing method, and weigh this up against real market data in a pursuit to find a correlation, should one exist. The paper found a sentiment-to-market accuracy 75%. And the accuracy score utilizing the rules-based approach of 72,72%.
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This project will deep into the motives and reasons behind cultural destruction. It will underline the will to entirely wipe off a distinctive group of population and its culture. Taking Syria as our main case given the events of the last decade; centring in the civil war where lives and art have been lost forever, together with the morale of its population, which fled to other countries in big numbers throughout the war. As for the perpetrators, ISIS will be the focus of our project, guilty of intentionally destroying many monuments, especially in Syria. Before explaining and answering to the questions of the project regarding culture, it is more than mandatory to analyse Syria’s history, tribes and regions. After reaching the core of our project and describing the possible reasons behind these actions, the third part of our project, which focuses on the emotional sphere of the victims. War brings with itself grief, loss, damage and destruction to a country and its material environment. To focus on the emotional attachment and emotional damage during this war shall be a matter of discussion nevertheless. We will not only analyse and discuss cultural destruction and the loss for humanity whenever perpetrators decide to damage forever something so important as our, as humans, common and singular past.
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This paper examines how Russian President Vladimir Putin incorporates the use of history in his speeches and articles with regards to how he positions Russia in its relation to Ukraine. The analysis is structured around three central places of remembrance (danish: erindringssteder): The Kyivan Rus which focuses on the close historical relation between Ukraine and Russia; the heritage of the Sovietunion in relation to how the union defined the borders of Soviet-Ukraine; World War II, ukrainian nationalism and its relation to nazism which centers around how Putin relates nazism to the current ukrainian political elite. The analysis concludes that Putin primarily utilizes the three places of remembrance to legitimize Russia's current invasion of Ukraine. Putin finds the distribution of territories during the soviet era to have been theft, and a complete violation of Russia's integrity. Furthermore, he seeks to protect ethnic russians within the borders of Ukraine from a genocide, instigated by ukrainian nationalists and neo-nazis, who continue the tradition of atrocities commited during World War II. Finally, Putin perceives Ukrainians and Russians as a single people, basing his claim on common history, language, and culture. Thus he implies that ukrainians should unite under Russia, as Russia is the more legitimate state.
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This paper revolves around the development of an LSTM multiclass classifier, constructed using Keras as framework and CRISP-DM as project process, with the purpose of classifying natural language into varying degrees of toxicity. The model takes a starting point in an existing toxic comment classification challenge from Kaggle.com, and makes a first iteration, engineered towards the requirements in the challenge. In this first iteration, several measures are taken to avoid common pitfalls of neural networks. The model is then held up against principles of freedom of speech including The Harm Principle and The Offence Principle by John Stuart Mill and Joel Feinberg respectively. After evaluating upon the models performance in the light of these principles, a second iteration is constructed with some design changes. For reasons i.a. related to the dataset, this operation is less successful. The paper concludes that it is possible to make a good multiclassification tool for shallow NLP problem, but gets less efficient in later iterations as we try to apply it to more concrete purposes.
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This project was set out to explore the role of the Turing Test in the development of Artificial Intelligence (AI), with emphasis on the historical perspective. This report contains an introductory presentation of the Turing Test and Artificial Intelligence. Furthermore, it presents two methods for analysis. The first method is a quantitative search in extracting the number of results from Google Scholars for search range between 1950 and 2019. The searched terms are ‘Turing Test’ and ‘Artificial Intelligence’. The second method is the one used for the analysis of two case studies, ELIZA and Google Duplex. In exploring the historical development, ELIZA is an early research topic from 1966 and Google Duplex is a contemporary project from 2018. This report concludes that the Turing Test appears to have played a role in the historical development of AI. Results from the quantitative search show that there is an exponential growth, followed by a short stabilisation, before it begins to decay towards the last decade. Both case studies failed when subjected to a strict Turing Test. Though when subjected to the Total Turing Test, Google Duplex seems to surpass it. Finally, this report also concludes that the Turing Test may no longer be relevant, as mediums for AI have evolved beyond text-based and most developments are no longer concerned with tricking humans.
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The main goal of the project will be to investigate to which extent ‘authentic’ culture isperformed. The main theories used, in order to obtain an understanding of culture andperception, will be Bourdieu’s Habitus, Butler’s Performativity and Goffman’s ImpressionManagement. The analysis will be structured around three different aspects: the object, thephenomenology and the discursive, connected by Brinkmann’s ontological triangle from TheEpistemology of Working with Everyday Life Materials. The theories will be applied in order toanalyze interactions made in Venice, by the group members, in order to determine to whichextent they had performed their culture, and how this can affect the ‘authenticity’ in culture.
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The project focuses on how the hungarian culture has been preserved throughout the years in the southeast region of Slovakia (Rye Island).
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This study explores the use of Natural Language Processing as a tool for online reviews. By drawing on theories about machine learning, this article investigates how to develop a Natural Language Processing model in Python. The authors present two machine learning models which were developed through an iterative design process and by implementing various approaches from the TRIN-model. This study concludes that machine learning models like ours might not have a significant impact on the future of reviews, but we are optimistic about the potential of Natural Language Processing as a tool for categorizing specific aspects of a company’s services. This conclusion is based on the analysis and discussion of the results we gathered from our Natural Language Processing models.
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This project examines the influence of the myth of Danish design on the consumption of Danish furniture. Danish design has historically been associated with qualities such as timelessness, craftsmanship, tradition and beauty and has played a significant role in the development of Danish society and culture. The construction of the category of modernist Danish design and its narratives was shaped by a social network of individuals and organizations, linking Danish design to notions of good taste and healthy living. Today, Danish design is praised for the same understated and high-quality features which legitimize its contemporary success.By drawing on Roland Barthes' theory of myth and Pierre Bourdieu's concept of cultural capital, this study investigates both the way in which the myth of Danish design is created, and consumed. The analysis combines a semiotic examination of Danish design mythology with a conceptual content analysis of interviews conducted by a Danish furniture company, Fredericia, as part of their celebration of Børge Mogensen's Folkestolen’s 75th anniversary.The findings reveal that the myth of Danish design influences the consumption of Danish furniture by communicating symbolic valuations associated with positive attributes such as beauty, timelessness, and fine craftsmanship. Simultaneously, the myth perpetuates ideological narratives that serve the interests of dominant power groups in society, including the Danish nation state, the furniture industry and even certain groups of consumers. The furniture industry strategically exploits the myth to drive desirability and capitalize on the associations carried within Danish design.This research underscores the sociocultural function of myth, which constructs markers of social, national, and personal identity. Danish furniture transcends its functional and aesthetic aspects, becoming a symbol of economic and cultural wealth and social status. Simultaneously, the myth of Danish design distorts ideological narratives around class dominance and power and naturalizes the notions of nationalism and Danishness into signifieds of tradition, health, functionalism, sustainability, and social accessibility. The analysis situates consumption within the context of cultural capital, modern mythology, and late-stage capitalism, highlighting the transformation of furniture into tools for managing self-identity, and signifiers of social status and taste. The holders of cultural capital benefit from perpetuating the myth of Danish design, securing both material and symbolic profits from ownership of Danish furniture. Thus the class elite utilizes its cultural competence to maintain its capital and power dominance in society, as cultural capital reproduces social structures.This research investigates the complex interplay between the myth of Danish design, the consumption of Danish furniture, and their sociocultural implications. By critically examining the myth's influence, this study offers insights into the mechanisms by which design narratives and cultural capital shape consumption and perpetuate power dynamics in society.
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This report illustrates the factors that influence the decision-making processes of individuals whentaking part in the contemporary art market, notwithstanding the risk often attributed to such asset and the economic uncertainty of periods such as the aftermath of Covid-19. By examining the motivations from different perspectives, this report aims to shed light on the dynamics of the contemporary art market and its resilience in the face of economic instability. To answer the research question what factors drive individuals in Denmark to take part in the contemporary art market amidst the current economic uncertainty? We carry out semi-structured interviews with two amateur art buyers, one curator, and two owners of renowned contemporary art galleries. The results show that investing in contemporary art 1) yields socio-economic advantages 2) is influenced by trust towards the artist, and 3) is a matter of familial background. The research emphasizes how these factors influences the perception of risk in the individuals when investing in a piece of contemporary art. The purpose of this study is to identify the key factors that affect participants' engagement with the art market by investigating their personal motivations, risk perceptions, and investment strategies. The research is also particularly useful and relevant given the current economic uncertainty and its potential effects on the investment landscape. The results of this study will add to the body of knowledge that exists aboutthe contemporary art investment market by giving a more in-depth and precise understanding of the factors that influence people to invest in art despite the current state of the economy.
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This paper, seeks to examine the correlation between stock price and public sentiment expressed through social media. Through twitter scraping and pre- processing, sentiment can be extracted from text. The paper will be based on a heuristic approach to natural language processing. Furthermore, the paper will rely on the most common forms of sentiment analysis, using a rule-based and a machine-learning approach as a starting point and weigh these up against each other. Finally, we will continue with the best performing method, and weigh this up against real market data in a pursuit to find a correlation, should one exist. The paper found a sentiment-to-market accuracy 75%. And the accuracy score utilizing the rules-based approach of 72,72%.
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This project will deep into the motives and reasons behind cultural destruction. It will underline the will to entirely wipe off a distinctive group of population and its culture. Taking Syria as our main case given the events of the last decade; centring in the civil war where lives and art have been lost forever, together with the morale of its population, which fled to other countries in big numbers throughout the war. As for the perpetrators, ISIS will be the focus of our project, guilty of intentionally destroying many monuments, especially in Syria. Before explaining and answering to the questions of the project regarding culture, it is more than mandatory to analyse Syria’s history, tribes and regions. After reaching the core of our project and describing the possible reasons behind these actions, the third part of our project, which focuses on the emotional sphere of the victims. War brings with itself grief, loss, damage and destruction to a country and its material environment. To focus on the emotional attachment and emotional damage during this war shall be a matter of discussion nevertheless. We will not only analyse and discuss cultural destruction and the loss for humanity whenever perpetrators decide to damage forever something so important as our, as humans, common and singular past.
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This paper examines how Russian President Vladimir Putin incorporates the use of history in his speeches and articles with regards to how he positions Russia in its relation to Ukraine. The analysis is structured around three central places of remembrance (danish: erindringssteder): The Kyivan Rus which focuses on the close historical relation between Ukraine and Russia; the heritage of the Sovietunion in relation to how the union defined the borders of Soviet-Ukraine; World War II, ukrainian nationalism and its relation to nazism which centers around how Putin relates nazism to the current ukrainian political elite. The analysis concludes that Putin primarily utilizes the three places of remembrance to legitimize Russia's current invasion of Ukraine. Putin finds the distribution of territories during the soviet era to have been theft, and a complete violation of Russia's integrity. Furthermore, he seeks to protect ethnic russians within the borders of Ukraine from a genocide, instigated by ukrainian nationalists and neo-nazis, who continue the tradition of atrocities commited during World War II. Finally, Putin perceives Ukrainians and Russians as a single people, basing his claim on common history, language, and culture. Thus he implies that ukrainians should unite under Russia, as Russia is the more legitimate state.
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This paper revolves around the development of an LSTM multiclass classifier, constructed using Keras as framework and CRISP-DM as project process, with the purpose of classifying natural language into varying degrees of toxicity. The model takes a starting point in an existing toxic comment classification challenge from Kaggle.com, and makes a first iteration, engineered towards the requirements in the challenge. In this first iteration, several measures are taken to avoid common pitfalls of neural networks. The model is then held up against principles of freedom of speech including The Harm Principle and The Offence Principle by John Stuart Mill and Joel Feinberg respectively. After evaluating upon the models performance in the light of these principles, a second iteration is constructed with some design changes. For reasons i.a. related to the dataset, this operation is less successful. The paper concludes that it is possible to make a good multiclassification tool for shallow NLP problem, but gets less efficient in later iterations as we try to apply it to more concrete purposes.
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