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Non-fungible tokens (NFTs) have become a popular topic in the art world in recent years, with many museums and other cultural institutions exploring ways to incorporate them into their operations. The technology has the potential to revolutionize how museums conduct their internal business, how they collect, display, and preserve digital art, as well as how they enable engagement and an immersive experience for visitors. The research question of this paper thus addresses the significance of NFTs in the evolution of museum practices.
Using a qualitative research approach, eleven museum experts were interviewed in semi-structured interviews about the evolution, the impact and the viability of NFTs. The results of the content analysis were then summarized, interpreted, and discussed in relation to the theoretical framework, and were subsequently converted into general conclusions for the museum sector. The process resulted in relevant information about the opportunities, challenges, and strategy of museums for implementing NFTs in museum practices.
As the information era progresses, the sheer volume of information calls for sophisticated retrieval systems. Evaluating them holds the key to ensuring the reliability and relevance of retrieved information. If evaluated with renowned methods, the measured quality is generally presumed to be dependable. That said, it is often forgotten that most evaluations are only snapshots in time and the reliability might be only valid for a short moment. Further, each evaluation method makes assumptions about the circumstances of a search and thereby has different characteristics. Achieving reliable evaluation is critical to retain the aspired quality of an IR system and maintain the confidence of the users. Therefore, we investigate how the evaluation environment (EE) evolves over time and how this might affect the effectiveness of retrieval systems. Further, attention is paid to the differences in the evaluation methods and how they work together in a continuous evaluation framework. A literature review was conducted to investigate changing components which are then modeled in an extended EE. Exemplarily, the effect of document and qrel updates on the effectiveness of IR systems is investigated through reproducibility experiments in the LongEval shared task. As a result, 11 changing components together with initial measures to quantify how they change are identifed, the temporal consistency of five IR systems could precisely be quantifed through reproducibility and replicability measures and the findings were integrated into a continuous evaluation framework. Ultimately, this work contributes to more holistic evaluations in IR.
This paper examines different business models of companies dealing with (earmarked) remittances and sheds light on the associated challenges of the industry, specifically, remittances for health, based on the model of the fintech startup GloryHealthCare. The work "Business Model Generation" by Osterwalder and Pigneur (2010) is used as a method for the analysis, as this is often used as a basis for the business models of startups. The study focuses regionally on Europe and Africa, as Germany and Ghana are the start-up's first target markets. Among other things, the industry's processes, pricing, and existing competition are examined. The SWOT analysis methodology clarifies the individual companies' opportunities and risks and makes a competitive position visible. Meanwhile, network effects of the diverse business models are made visible based on the paper "Digital Economy and Network Effects" by Frank Linde (2020). Network effects play a crucial role in the reach, influence, and competitiveness of existing and new businesses in the remittance industry. The study also emphasizes the importance of knowledge and networks, which are more important than financial resources. The previous aspects considered a basis for developing a new concept as an alternative to the Business Model Canvas: the iBusiness Model. The results of this study provide insights into the design of efficient business models and support companies in the remittance industry in developing strategies to overcome challenges and take advantage of opportunities.
This thesis aims to extend an existing Open Educational Resource (OER), which is available as a GitHub repository, and provide an organized introduction to basic machine learning (ML) concepts and algorithms. Further models, followed by structured metadata for each object, will be included while adhering to the contribution guidelines of the OER and following the CC license. The Machine-Learning-OER Basics repository intends to provide a wide range of benefits by enabling diverse users to apply and distribute machine learning algorithms. The goal of this digital collection is to fill the existing gap for instructional material on using machine learning in OER as well as make it easier to learn ML concepts effectively. These ML models are developed using the programming language Python and the library scikit-learn, among other standard libraries. Jupyter Notebook will make it straightforward for the user to explore the code. In order to apply the models to various practical scenarios, a non-specific data set is selected. This work is considered a solution approach in that it includes adding classification models.
A performance comparison of the models is conducted. This comparative analysis evaluates the efficiency of each model. The examination includes various metrics for measurement. This work serves as a written extension, providing comprehensive background information on the algorithms utilized within the repositories and the performance comparison.
As a result of the widespread use of online networking sites, the ways in which people connect and network, both personally and professionally, have been transformed in recent years. Platforms such as LinkedIn or XING have profoundly changed the dynamics of professional networking by providing new means of contact and creating an environment that promotes the exchange of knowledge and ideas. However, compared to social network sites, professional network sites have received little attention in research despite their growing importance. Particularly, the relationship between the use of professional network sites and users' well-being has been understudied. However, the investigation of these platforms is of societal relevance given their consistent growth and the increasing importance of these platforms for both individuals and companies. Existing research on the relationship between the use of social network sites (SNS) and the subjective well-being of users has identified the usage type (active and passive use) as a relevant variable. The aim of this study was to transfer these findings to the context of professional network sites and to explore the relationship between the type of use of a professional network site and the subjective well-being of its users.For this purpose, the active-passive model of SNS use was applied to the context of professional network sites for the first time. To answer the research question, a quantitative online survey was conducted with 526 LinkedIn users. Results of the mediation analyses revealed an indirect positive relation between active use of LinkedIn and well-being. Conversely, a negative indirect relation was found between passive use of LinkedIn and subjective well-being. All tested mediating variables, including social capital for active use and upward social comparison, downward social comparison and envy for passive use, were determined to be relevant in explaining the link between well-being and active and passive LinkedIn use, respectively.
In the second decade of the 21st century, far-right ideas and groups have made themselves present and active in politics in the west, even winning local and national elections in some countries, such as the United States, Brazil and Hungary. While having specific ideological and cultural differences in its many forms in different countries, the far-right movement on an international scale has proven to be similar in its core and tactics.
This new-born far-right is in essence populist, defends conservative values, and navigates in what in popular use - and to some extent in academic discourse - is called post-truth politics. The concept of post-truth politics can be summarized as an increasing disregard to factual evidence in political discourse and decision-making. As the term “post-truth” suggests, facts regarding what is in discussion and the opinion of experts are secondary, if important at all, in comparison to emotional aspects being communicated. The condition for the success of the message is its appeal to the listener’s beliefs and values. Given this conjecture, conspiracy theories and science denialism can be powerful rhetorical tools in political discourse. A politician who constantly communicates using these tactics is Brazilian President Jair Bolsonaro. Since before he was elected, the then candidate had always been heavily present in social media and been accused of spreading disinformation and fake news on his online profiles, which continued during his term. As the Covid-19 pandemic started, the executive organ of the Brazilian government minimized the importance and gravity of the situation in disregard to the orientation of the massive majority of the scientific community. In October 2021 Brazil reached over 600.000 deaths by COVID since the beginning of the pandemic, according to official data, which makes the country the 7th on the ranking of deaths per million.
This thesis aims to, firstly, discuss the interaction and causes of the rise of the far-right, post-truth politics, social media and the communication of conspiracy theories and science denialism in political discourse in general, but also to go deeper in the Brazilian context, in order to understand the events that lead to President Bolsonaro’s election, his ideology, rhetoric and communication. The second goal of this thesis is to identify conspiracy theories and science denialism in the official communication of the Brazilian government in regard to the COVID-19 pandemic; classify the content according to the structure of conspiracy theorization and science denialism; and analyze these findings within the scope of interactions described in the first part of the thesis. The third goal of this thesis is to discuss the findings of the second part and the outcomes (deaths, vaccination rate and willingness, adoption and disrespect of public health measures) of the pandemic in Brazil so far and to suggest topics for further research.
The purpose of this research lies in uncovering the participants emotions when watching a personalized advertisement on the social media Instagram. This is of use to the marketing and psychology research community to discover more on consumer behavior and the controversy between privacy concerns and usefulness of advertisement personalization. The research question reads: “Does the use of personalization on social media advertisements incite (1) a change in the emotional state and (2) recall capability of German Instagram users aged 18-30 that diverges from the psychophysiological parameters measured by exposing these users to the same advertisements without personalization?”
Psychophysiological tests are used in combination with two self reported questionnaires that assess the participants positive and negative effect and the recall and recognition differences between the group given personalized stimuli including the participants name, location, and activity and the one group given impersonalized ones. The sample consists of n=31 German-speaking participants between the age of 18 and 30.
The results, although not all of statistic relevancy of α=0,05, show a trend that personalized advertisements instigate more positive valence and activation as not personalized stimuli. No significant or trending difference was found to the recall and recognition capabilities of the two groups.
As a key part of human-computer interaction(HCI) and usability testing, the capturing and recording of key user interaction plays a center role for ensuring a reliable post-hoc analysis of collected user interaction data, thus improving the odds of insightful HCI and usability testing cycles for use cases such as the evaluation of interactive information retrieval Systems(IRR). As such, the practice of logging is of significant importance for multiple fields of study such as IIR, HCI and most recently also Living Lab approaches. Living lab approaches represent a user-centered research methodology with a focus on user involvement, experimental approaches and extensive collaboration for the sake of co-production of knowledge and as such, has a dire need for robust and easy to use logging solutions.
With past logging solutions being either expensive, hard to use or error-prone, recent conferences gave rise to new logging solutions using contemporary web technologies, which aim to improve the logging landscape within the research community. Over the course of this paper, two of these recent logging solutions, LogUI and Big Brother, are to be inspected for their key features and then evaluated, whether they are suitable logging solutions for living lab and IIR environments. Results and research indicate, that both logging solutions offer significant benefits for research using living lab and IIR approaches, with LogUI embracing many of the experimental paradigms that guide the living lab approach.
Relevance: Political and private initiatives call for more female founders in start-ups as well as entrepreneurship but with regard to academic research not many studies focused yet on interdisciplinary studies on especially female start-up founders. There is more need to understand the topic to further encourage female founders.
Research question: The research question of this thesis is analysing what kind of patterns can be seen in the entrepreneurial, sociocultural and psychological profile of female founders compared in start-up ecosystems of three different countries, namely Germany, France and Israel?
Approach: I conducted 21 interviews, seven for each city, with a semi-structured guideline focusing on the entrepreneurial, sociocultural and psychological profile. The interviews were transcribed and afterwards analysed by combining the different profiles to find possible patterns. In a final step the observations from each country were compared to one another.
Findings: There are several possible patterns for each country evident. However, a cross-cultural comparison was made difficult by the heterogeneous groups of respondents. It was nevertheless possible to conclude on four crosscultural hypotheses: 1) Female entrepreneurs prefer to work first before starting their own business; 2) The female entrepreneurial profile is risk-taking, purpose-driven, innovative and autonomous; 3) Immigration has a positive effect on the intention to start a business; 4) The majority of female entrepreneurs have a higher education and come from a middle to upper social class.
Digitalisation is shaping a new consumption era characterised by high connectivity, mobility and a broad range of easily accessible information on products, prices and alternatives. As a result, it becomes more difficult than ever to understand modern consumers along their complex and dynamic path to purchase. However, mobile data about consumers’ behaviour captured on their phone has high potential for facing this challenge. Yet, there is no solution on how to use this data to follow the consumers on their mobile devices. This thesis proposes a first approach on how mobile data collected with smartphone sensing technology can be analysed to assess mobile consumer behaviour along their customer journey. Based on current practices in customer journey analytics, a mobile customer journey model is developed and three analysis concepts are created, which are implemented in an explorative analysis. The results show that mobile sensing data presents a great opportunity for analysing mobile behaviour in three main research areas: examining the touchpoint performance of a brand across mobile apps, describing different target groups by their smartphone usage behaviour and deriving real customer journeys on users’ devices. Nonetheless, further exploration is necessary to unlock the full potential of mobile data in customer journey analytics.