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This Bachelor’s Thesis discusses the Swedish artist and photographer Birger Gabriel Sjöberg. He was born in Varberg, Sweden in the year of 1835 and died 40 years later, in the year of 1875. During his short-lived life he accomplished creating both paintings and photographs connected to his hometown. These are now of value by culture-historical means. By answering question formulations regarding his living, education and esthetic production, the main purpose is to give a synoptic presentation of both his life and work. Since Sjöberg is not a part of the widely known context of art history, the thesis also strives to bring a light to a mostly unknown and unwritten artist. This study contains of two main parts, one biographical part, and one iconological part were a chosen number of his paintings and photographs are discussed. Throughout the iconological part, the works are analysed by means of Heinrich Wölfflin’s Principles of Art History. The introducing of the works is to give an overall apprehension about what he achieved concerning his creating in both work and private life.

Macroeconomic forecasting is a classic problem, today most often modeled using time series analysis. Few attempts have been made using machine learning methods, and even fewer incorporating unconventional data, such as that from social media. In this thesis, a Generative Adversarial Network (GAN) is used to predict U.S. unemployment, beating the ARIMA benchmark on all horizons. Furthermore, attempts at using Twitter data and the Natural Language Processing (NLP) model DistilBERT are performed. While these attempts do not beat the benchmark, they do show promising results with predictive power. The models are also tested at predicting the U.S. stock index S&P 500. For these models, the Twitter data does improve the accuracy and shows the potential of social media data when predicting a more erratic index with less seasonality that is more responsive to current trends in public discourse. The results also show that Twitter data can be used to predict trends in both unemployment and the S&P 500 index. This sets the stage for further research into NLP-GAN models for macroeconomic predictions using social media data. Makroekonomiska prognoser är sedan länge en svår utmaning. Idag löses de oftast med tidsserieanalys och få försök har gjorts med maskininlärning. I denna uppsats används ett generativt motstridande nätverk (GAN) för att förutspå amerikansk arbetslöshet, med resultat som slår samtliga riktmärken satta av en ARIMA. Ett försök görs också till att använda data från Twitter och den datorlingvistiska (NLP) modellen DistilBERT. Dessa modeller slår inte riktmärkena men visar lovande resultat. Modellerna testas vidare på det amerikanska börsindexet S&P 500. För dessa modeller förbättrade Twitterdata resultaten vilket visar på den potential data från sociala medier har när de appliceras på mer oregelbunda index, utan tydligt säsongsberoende och som är mer känsliga för trender i det offentliga samtalet. Resultaten visar på att Twitterdata kan användas för att hitta trender i både amerikansk arbetslöshet och S&P 500 indexet. Detta lägger grunden för fortsatt forskning inom NLP-GAN modeller för makroekonomiska prognoser baserade på data från sociala medier.

AbstractThousands of Roma were killed in Ukraine by the Nazis and auxiliary police on the spot. There are more than 50,000 Roma in today’s Ukraine, represented by second and third generation decendants of the genocide survivors. The discussion on Roma identity cannot be isolated from the memory of the genocide, which makes the struggle over the past a reflexive landmark that mobilizes the Roma movement. About twenty Roma genocide memorials have been erected in Ukraine during last decade, and in 2016 the national memorial of the Roma genocide was opened in Babi Yar. However, scholars do not have a clear picture of memory narratives and memory practices of the Roma genocide in Ukraine. A comprehensive analysis of the contemporary situation is not possible without an examination of the history and memory of the Roma genocide before 1991.

How do students use schools´ history education to develop their historical consciousness? In which ways could history education be regarded as a historical-culture expression, i.e. as a part of a society’s interest in the past? This thesis takes its point of departure in these overarching questions. More specifically the research was carried out as a contextualised case study of sixteen history lessons in a Swedish Year 9 class, in the autumn of 2009. The contextualisation consists of an analysis on historical-culture expressions in Sweden at that time. Despite conflicting opinions, the major finding was the common view of Sweden as a country that solves her problems in a peaceful way, both in the past, the present and the future. The classroom study was conducted with an ethnographical approach with close attention to teacher-student interactions. The research was guided by an analytical model inspired by the historian Jörn Rüsen’s theories on history learning processes. The results show in detail the complicated learning processes in the classroom but also the connection with the historical-culture expressions in Sweden at that moment. One major finding was the tendency to react to the rise of contemporary islamophobia and nationalism in Sweden by making comparisons with the development in Weimar Germany in the beginning of the 1930s. This tendency was present both in and outside the classroom. Hur använder elever skolans historieundervisning för att utveckla sitt historiemedvetande? På vilka sätt kan genomförd historieundervisning betraktas som en ”historiekulturell yttring” i ett samhälle? Den här avhandlingen tar sin utgångspunkt i dessa och andra övergripande frågor som rör unga människors behov av tidslig orientering i början av 2000-talet. Avhandlingen bygger på en historiedidaktisk fallstudie av en serie lektioner i en åk 9-klass. I centrum för analyserna står lektionernas pågående historiska lärande. Men studien intresserar sig också för förbindelser mellan den analyserade undervisningen och andra historiekulturella yttringar i Sverige utanför klassrumsdörren vid denna tidpunkt, hösten 2009. Av studien framgår hur eleverna genom undervisningen erbjuds möjligheter att aktivera sitt historiemedvetande, men också hur sammansatta historieämnets lärprocesser kan vara på högstadiet. Samtidigt visar studien att klassrummets berättelser om 1900-talet som ”katastrofernas århundrade” verkar stå i nära förbindelse med en schematisk ”mönsterberättelse” om Sverige som ett land som kan hantera förflutna fasor, en osäker samtid och en hotande framtid.

Syftet med denna uppsats är att diskutera några av de minnespraktiker i efterdiktaturens Argentina som behandlar det kollektiva minnet av det Smutsiga Kriget och de som blev utsatta för tvångsförsvinnande. Praktikerna som studerats är Madres de Plaza de Mayo, minnesplatser upprättade i före detta fångläger och Parque de la Memoria. Uppsatsen anknyter till ett teoretiskt ramverk för kollektivt minne och kollektivt trauma, minnesmuseer och materiell kultur. Studien har utformats som en fallstudie. Materialet består av observationer, intervjuer och fotografier insamlade under fältarbete i Argentina 2017. Madres de Plaza de Mayo analyserades genom att använda teorier om lieux de mémoire framförda av Pierre Nora och minnesceremonier framförda av Paul Connerton. Minnesplatserna studerades utifrån ett minnesmuseumsperspektiv med hjälp av teorier av Paul Williams. Parque de la Memoria studerades utifrån teorier om krigsmonument framförda av Jay Williams. Madres de Plaza de Mayo kan förstås som lieu de mémoire eftersom de i sina artikulationer och aktioner är materiella, symboliska och funktionella. Genom dem bevaras de försvunna vid liv. Minnesplatserna presenterar ett mer ambivalent narrativ som placerar de försvunna i limbo. Parque de la Memoria är en plats för sorg och för att offentligt hedra dem som föll offer under det Smutsiga Kriget. Kontexten som dessa praktiker befinner sig i är komplex och de olika praktikerna uttrycker tre olika narrativ över de försvunna, som sträcker över spektrumet från liv till död. Detta är en tvåårig mastersuppsats i ämnet musei- och kulturarvsvetenskap The purpose of this thesis is to discuss some of the memory-practices in post-dictatorial Argentina regarding the collective memory of the Dirty War and the people who were objects of forced disappearances. The practices studied are Madres de Plaza de Mayo, sites of memory established in former centres of detention and Parque de la Memoria. The thesis draws upon the theoretical framework of collective memory and collective trauma, memorial museums and material culture. The study was formed as a case study. The materials are observations, interviews and photographs, and were gathered through field work in Argentina in 2017. The Madres de Plaza de Mayo were analysed using theories on lieux de mémoire brought forward by Pierre Nora and commemoration ceremonies brought forward by Paul Connerton. The sites of memory were studied out of the perspective on memorial museums by Paul Williams. Parque de la Memoria was studied with theories on war memorials by Jay Winter. The Madres de Plaza de Mayo can be interpreted as lieu de mémoire due to their material, symbolic and functional dimensions. Through them, the disappeared are alive. The sites of memory present an ambivalent narrative. The narrative of the disappeared is that of a state of limbo. Parque de la Memoria is a park of mourning, placing the disappeared in a narrative of death. The situation of memory-practices in post-dictatorial Argentina is complex and the practices articulates three different narratives of the disappeared, ranging from life to death. This is a two-year master’s thesis in Museum and Cultural Heritage Studies

The purpose of this thesis is to investigate different scales of mobility and social networks in Southern Scandinavia around 7000 BC. An essential basis for this work is the hypothesis that the conical core pressure blade technology, a specific method for producing lithic blades, reached Scandinavia from the east. The process has been discussed and verified in several earlier studies. The study is based on investigations of lithic material and bone tools, as well as human skeletal remains; a multidisciplinary strategy has been applied, which combines technological analyzes of archaeological material with isotope analyzes of human teeth. Materials and data have been collected from a total of 111 sites located mainly in Scandinavia, but also in Finland, the Baltic countries and Russia. The Mesolithic site Norje Sunnansund in Blekinge, southern Sweden is in focus. Analyzes of the chaîne opératoire of lithic and osseous production make it possible to study technological processes as the transmission of culturally conditioned patterns; these patterns underlie the formative principles of each technology complex. By identifying specific traditional knowledge built into the material process, it becomes possible to define prehistoric human traditions and thereby study human interactions and migrations between geographical regions. The analyzes of strontium isotopes in human teeth from Norje Sunnansund enables an additional individual provenancing since the isotopes reflect a geographical-geological variation. The study provides a higher resolution of the arrival and spreading of the pressure blade technology from the northeast. It also strengthens the picture of a Mesolithic society in Southern Scandinavia based on geographically extensive social networks. An increased regionalization and territorialization has previously been proposed for western Scandinavia around 8800-7500 BC. The study confirms that during this period the population seem to consist of several subgroups related to specific territories, but with close and regular contact within a more extensive social network. This fits well with the picture of a group that may have inhabited Norje Sunnansund for extended periods, while social contacts were maintained over longer distances.

The Zebra’s Voice special edition “Botswana Museum@50. Celebrating Our National Heritage”

In this thesis, various machine learning domains have been combined in order to build a video recommender system that is based on object detection. The work combines two extensively studied research fields, recommender systems and computer vision, that also are rapidly growing and popular techniques on commercial markets. To investigate the performance of the approach, three different content-based recommender systems have been implemented at Spotify, which are based on the following video features: object detections, titles and descriptions, and user preferences. These systems have then been evaluated and compared against each other together with their hybridized result. Two algorithms have been implemented, the prediction and the top-N algorithm, where the former is the more reliable source for evaluating the system's performance. The evaluation of the system shows that the overall performance scores for predicting values of the users' liked and disliked videos are in the range from about 40 % to 70 % for the prediction algorithm and from about 15 % to 70 % for the top-N algorithm. The approach based on object detection performs worse in comparison to the other approaches. Hence, there seems to be is a low correlation between the user preferences and the video contents in terms of object detection data. Therefore, this data is not very suitable for describing the content of videos and using it in the recommender system. However, the results of this study cannot be generalized to apply for other systems before the approach has been evaluated in other environments and for various data sets. Moreover, there are plenty of room for refinements and improvements to the system, as well as there are many interesting research areas for future work.

The use cases of Information Extraction (IE) are more or less endless, often consisting of a combination of Named Entity Recognition (NER) and Relation Extraction (RE). One use case of IE is the extraction of transaction information from Norwegian insider transaction Press Releases (PRs), where a transaction consists of at most four entities: the name of the owner performing the transaction, the number of shares transferred, the transaction date, and the price of the shares bought or sold. The relationships between the entities define which entity belongs to which transaction, and whether shares were bought or sold. This report has investigated how a pair of supervised NER and RE models extract this information. Since these Norwegian PRs were not labeled, two different approaches to annotating the transaction entities and their associated relations were investigated, and it was found that it is better to annotate only entities that occur in a relation than annotating all occurrences. Furthermore, the number of PRs needed to achieve a satisfactory result in the IE pipeline was investigated. The study shows that training with about 400 PRs is sufficient for the results to converge, at around 0.85 in F1-score. Finally, the report shows that there is not much difference between a complex RE model and a simple rule-based approach, when applied on the studied corpus.