Analysing social media data using sentiment analysis in relation to public order

The research aim is to analyse social media data using sentiment analysis in relation to public order. A sentiment can be expressed in a thought, opinion or attitude that is mainly based on emotion instead of reason. (SA) Sentiment Analysis studies the opinions, sentiments and emotions expressed at sentence or document level. SA extracts text which is identified and classified as opinions or emotions that aim to support a decision-making process through the analysis of text. SA identifies and measures whether the text being analysed is positive, negative or neutral in relation to an entity, such as people, organisation, event, location, or a topic. As the adoption of ubiquitous technology increases and the population on social media continues to grow with the speed of responsiveness of the users expressing their political, economic or religious views on Twitter or Facebook, the posts become valuable sources of public opinion. This can be seen as an important commodity to be used to infer public opinions for social studies or marketing. The research suggests the police have found it difficult to adapt their existing model to the changing nature of public events and handling of acceleration towards technology and social media. The scalability and volume of data has made it increasingly hard for the police to manage, monitor and make use of intelligence emerging from social media to maintain the peace. To address this gap, the investigation will evaluate whether SA can enhance the analysis of social media in the context of public (dis)order events. This may help to improve the police’s decision-making process and reduce complexity to increase public safety. There are specific and generalised ways that SA can support the police, but this research might focus on a specific case. To meet the aim, the research proposes to use a SA model, data mining tools and techniques to analyse the relevant data extracted from social media. The project will use an adapted social media lifecycle as a methodological approach. Past events involving public order and the police will be evaluated to develop relevant methodology and provide appropriate recommendations to the technical community on ways to use SA for future applications of social media. In the project it adopted a hybrid approach which consists of a dictionary, machine learning and gold standard approaches. As result, the machine learning of dictionaries and manual classification results proved to show the strongest output based on precision, recall and F1 measure when compared to the machine learning of tweets and manual classification. The change point analysis helped to identify significant points in the timeline of tweets for the event which correlated to the physical event. However, there were some inaccuracies on the allocated points of change, as deemed insignificant based on news media and low volume of tweets. Future work is required to understand the reasons behind the allocation change points and possible use of alternative methods to help extract further insights that could not be explored in this project. The study makes a series of contributions to knowledge. First, to the creation of a keywords for public order events due to none being publicly available. Second, is to build towards a model to predict what may happen in public order events with the application of dictionary, machine learning and creation of gold standard in the realm of sentiment analysis. Third, the technical contribution to sentiment analysis community to help provide future recommendations to potentially enhance their framework and what areas require further research in the area. Fourth, is the development of social media lifecycle methodology, which has been tested in this project

2016 Oklahoma Research Day Full Program

This document contains all abstracts from the 2016 Oklahoma Research Day held at Northeastern State University

Neolithic land-use in the Dutch wetlands: estimating the land-use implications of resource exploitation strategies in the Middle Swifterbant Culture (4600-3900 BCE)

The Dutch wetlands witness the gradual adoption of Neolithic novelties by foraging societies during the Swifterbant period. Recent analyses provide new insights into the subsistence palette of Middle Swifterbant societies. Small-scale livestock herding and cultivation are in evidence at this time, but their importance if unclear. Within the framework of PAGES Land-use at 6000BP project, we aim to translate the information on resource exploitation into information on land-use that can be incorporated into global climate modelling efforts, with attention for the importance of agriculture. A reconstruction of patterns of resource exploitation and their land-use dimensions is complicated by methodological issues in comparing the results of varied recent investigations. Analyses of organic residues in ceramics have attested to the cooking of aquatic foods, ruminant meat, porcine meat, as well as rare cases of dairy. In terms of vegetative matter, some ceramics exclusively yielded evidence of wild plants, while others preserve cereal remains. Elevated δ15N values of human were interpreted as demonstrating an important aquatic component of the diet well into the 4th millennium BC. Yet recent assays on livestock remains suggest grazing on salt marshes partly accounts for the human values. Finally, renewed archaeozoological investigations have shown the early presence of domestic animals to be more limited than previously thought. We discuss the relative importance of exploited resources to produce a best-fit interpretation of changing patterns of land-use during the Middle Swifterbant phase. Our review combines recent archaeological data with wider data on anthropogenic influence on the landscape. Combining the results of plant macroremains, information from pollen cores about vegetation development, the structure of faunal assemblages, and finds of arable fields and dairy residue, we suggest the most parsimonious interpretation is one of a limited land-use footprint of cultivation and livestock keeping in Dutch wetlands between 4600 and 3900 BCE.NWOVidi 276-60-004Human Origin

Taphonomy, environment or human plant exploitation strategies?: Deciphering changes in Pleistocene-Holocene plant representation at Umhlatuzana rockshelter, South Africa

The period between ~40 and 20 ka BP encompassing the Middle Stone Age (MSA) and Later Stone Age (LSA) transition has long been of interest because of the associated technological change. Understanding this transition in southern Africa is complicated by the paucity of archaeological sites that span this period. With its occupation sequence spanning the last ~70,000 years, Umhlatuzana Rock Shelter is one of the few sites that record this transition. Umhlatuzana thus offers a great opportunity to study past environmental dynamics from the Late Pleistocene (MIS 4) to the Late Holocene, and past human subsistence strategies, their social organisation, technological and symbolic innovations. Although organic preservation is poor (bones, seeds, and charcoal) at the site, silica phytoliths preserve generally well throughout the sequence. These microscopic silica particles can identify different plant types that are no longer visible at the site because of decomposition or burning to a reliable taxonomical level. Thus, to trace site occupation, plant resource use, and in turn reconstruct past vegetation, we applied phytolith analyses to sediment samples of the newly excavated Umhlatuzana sequence. We present results of the phytolith assemblage variability to determine change in plant use from the Pleistocene to the Holocene and discuss them in relation to taphonomical processes and human plant gathering strategies and activities. This study ultimately seeks to provide a palaeoenvironmental context for modes of occupation and will shed light on past human-environmental interactions in eastern South Africa.NWOVidi 276-60-004Human Origin

Ways and Capacity in Archaeological Data Management in Serbia

Over the past year and due to the COVID-19 pandemic, the entire world has witnessed inequalities across borders and societies. They also include access to archaeological resources, both physical and digital. Both archaeological data creators and users spent a lot of time working from their homes, away from artefact collections and research data. However, this was the perfect moment to understand the importance of making data freely and openly available, both nationally and internationally. This is why the authors of this paper chose to make a selection of data bases from various institutions responsible for preservation and protection of cultural heritage, in order to understand their policies regarding accessibility and usage of the data they keep. This will be done by simple visits to various web-sites or data bases. They intend to check on the volume and content, but also importance of the offered archaeological heritage. In addition, the authors will estimate whether the heritage has adequately been classified and described and also check whether data is available in foreign languages. It needs to be seen whether it is possible to access digital objects (documents and the accompanying metadata), whether access is opened for all users or it requires a certain hierarchy access, what is the policy of usage, reusage and distribution etc. It remains to be seen whether there are public API or whether it is possible to collect data through API. In case that there is a public API, one needs to check whether datasets are interoperable or messy, requiring data cleaning. After having visited a certain number of web-sites, the authors expect to collect enough data to make a satisfactory conclusion about accessibility and usage of Serbian archaeological data web bases