Studies of K-pop fandom culture : User experience and motive research of subscription app “Bubble”

The digitalization of music has caused a significant change in the economics and logistics of the music industry. With the introduction of subscription-based music streaming services, music has become more accessible compared to the time when it was distributed and consumed in physical form. However, the sustainability of streaming services for artists has been a topic of debate for many years. During my studies at UiA, I attended the Kristiansand Roundtable Conference in 2022 and one of the most memorable quotes I heard was "A single T-shirt merch sale are equivalent of the same profit as three years' worth of non-stop streaming of one song."(KRC2022) This highlights the fact that being an artist is a career path that requires extra effort to make a living and support one's career. Given the complexity of the economics of music, finding additional ways to create revenue may be a viable solution as music lost its scarcity. Every Morning, we open our eyes to new types of concepts we haven’t faced before. Creativity and artificial intelligence, NFTs, artists and music in metaverse and virtual reality. While technological innovation brings new challenges to adopt in the music industry on a daily basis,“What does it take not just to survive, but to thrive?” (Hughes et al, 2016,p.4) As one of the viable revenue streams to research, I selected one specific service that has been operating in South Korea that is rooted from K-pop fan culture - fan apps. These apps are either developed by external companies or acquired tech companies, and they offer fans exclusive content and opportunities to interact with their favorite artists and fellow fans. While there are various aspects to these apps, I will focus on two main functions. The first is their potential to generate revenue in various areas such as merch sales, marketing, ticketing, and as a platform to bring fans into the concept of the metaverse . The second is their ability to generate thriving income through communication. For instance, in 2020, revenue from an app called 'bubble' was approximately 7.3 million euros. However, with steady growth, the revenue reached over 32.3 million euros in 2022, with a yearly growth rate of over 30%. Observing this tremendous growth has The purpose of this research is to aid understanding of fan cultures and finding factors that encourage proactive fan behaviors in case studies of K pop fan apps, in order to utilize these emotional designs of artist- fan relationships for other artists. In this thesis, my research will be divided into two sections. First I will provide background information of three major apps (Weverse,bubble,Universe) including their finance, feature, artist pool. Second, I will demonstrate ethnographic and qualitative research of user experience on app Bubble, to provide users motivation and factors that differentiate this specific service to other social media platforms

Electron transitions and propagation characteristics of dipolarization fronts observed by cluster

This thesis describes electron transitions at the dipolarization fronts (DPFs) observed by Cluster using high time-resolution data. The sharp electron transitions occur within the rising phase of the magnetic field component Bz normal to the magnetotail current sheet. The electron transitions provide a new constraint on the DPFs generation models that are related to reconnection. A sudden Bz rise without a small dip prior to the increase was observed suggesting that tearing instabilities in the reconnection exhaust may not be required for the generation of DPFs. Based on timing and minimum variance analysis, the DPFs are found to have a curved structure and propagate earthward. The results in this study are consistent with DPFs being the injection fronts from the reconnection exhaust

The contested politics of the Asian atom: a comparative analysis of peripheralisation and nuclear power in South Korea and Japan

South Korea and Japan have adhered to an unwavering commitment to a nuclear-focused energy supply system despite the contested nature of that technology and the unprecedented Fukushima accident in 2011. In this study, we explore the socio-political consequences of four nuclear-related facilities (Ulju, Gyeongju, Futaba, and Rokkasho) through the lens of social peripheralisation. This framework suggests that nuclear facilities will migrate to communities that are geographically remote, economically marginal, politically powerless, culturally defensive, and environmentally degraded. We expand and test this framework in two ways: moving beyond the UK (where it was developed) and moving beyond only nuclear waste repositories (to include reactors, fuel processing, on-site storage, and other elements of the lifecycle). We find that nuclear infrastructures in our four cases are imposed on peripheral regions, impairing not only the structure of local economies and political power, but also creating a discriminative structure in terms of social and environmental inequality. Peripheralisation suggests a deeper dynamic by which pro-nuclear attitudes become “locked in” socially and culturally so that communities come to depend on the very processes that made them peripheral. Community dynamics, subnational struggles, and contests over local power relations may determine the future of nuclear power

Delineation of high resolution climate regions over the Korean Peninsula using machine learning approaches

In this research, climate classification maps over the Korean Peninsula at 1 km resolution were generated using the satellite-based climatic variables of monthly temperature and precipitation based on machine learning approaches. Random forest (RF), artificial neural networks (ANN), k-nearest neighbor (KNN), logistic regression (LR), and support vector machines (SVM) were used to develop models. Training and validation of these models were conducted using in-situ observations from the Korea Meteorological Administration (KMA) from 2001 to 2016. The rule of the traditional Koppen-Geiger (K-G) climate classification was used to classify climate regions. The input variables were land surface temperature (LST) of the Moderate Resolution Imaging Spectroradiometer (MODIS), monthly precipitation data from the Tropical Rainfall Measuring Mission (TRMM) 3B43 product, and the Digital Elevation Map (DEM) from the Shuttle Radar Topography Mission (SRTM). The overall accuracy (OA) based on validation data from 2001 to 2016 for all models was high over 95%. DEM and minimum winter temperature were two distinct variables over the study area with particularly high relative importance. ANN produced more realistic spatial distribution of the classified climates despite having a slightly lower OA than the others. The accuracy of the models using high altitudinal in-situ data of the Mountain Meteorology Observation System (MMOS) was also assessed. Although the data length of the MMOS data was relatively short (2013 to 2017), it proved that the snowy, dry and cold winter and cool summer class (Dwc) is widely located in the eastern coastal region of South Korea. Temporal shifting of climate was examined through a comparison of climate maps produced by period: from 1950 to 2000, from 1983 to 2000, and from 2001 to 2013. A shrinking trend of snow classes (D) over the Korean Peninsula was clearly observed from the ANN-based climate classification results. Shifting trends of climate with the decrease/increase of snow (D)/temperate (C) classes were clearly shown in the maps produced using the proposed approaches, consistent with the results from the reanalysis data of the Climatic Research Unit (CRU) and Global Precipitation Climatology Centre (GPCC)