Social Event Analysis Research Articles

Proses Sosiokultural Siswa Dalam Pendidikan Multikultural di Sekolah Dasar

The purpose of this research is to look at students' sociocultural processes in multicultural education in elementary schools. This research is a type of qualitative research with a phenomenological approach, namely by conducting a critical analysis of social events. Data collection techniques are carried out by observation, interviews, and documentation. The results of the study show that at SD SD Negeri 008 Sidodadi the teachers have integrated students' socio-culture into multicultural education through a learning model at school. This is seen as important to provide provision and help develop insight into thinking and personality and to train students in dealing with social problems that occur in their community environment.

Feasibility of the Goal of Sociology under Its Current Methodology

Sociology has attained a prominent status in the modern world, due to the role it played in the analysis of contemporary social issues and events. This has attracted an increasing interest in sociology not only in the Westerns societies, but also in the Muslim world due to their desire for modernization. Therefore, this article attempts to analyse whether sociology can attain its goal of reorganizing society, based on scientific methods. It also analyses ethics and morality as alternative means for the purpose, and as a source of derivation of universal rule of human social behaviour hence, reorganization of society. This research is theoretical and philosophical and uses a qualitative method as it relies on the analysis of the data gathered from textual sources. Using an analytical approach, the writers arrive at the conclusion that Sociology under its current scientific methodology, cannot achieve its goal of reorganizing society. This can be attributed to inadequacy of scientific method in the study of human society, due to the unpredictability of human behaviour and variety of its factors. The writers also suggest the adaptation of a dynamic multidimensional method that consider variety of factors such as spiritual, physical, mental, social, and moral which heavily influence human behaviour.

Epidemiology and risk factors of trichinellosis in Bosnia and Herzegovina from 1961 to 2021

This study is a retrospective analysis of social, economic, political, and cultural events on the annual incidence of trichinellosis in Bosnia and Herzegovina (BiH). It highlights the importance of specific regulations, which have been incorporated into developing preventive protection against this human disease for the last 61years since it has been monitored by law. In the period, 1961-2021, 3828 people became infected. The first outbreak of trichinellosis was documented in 1965, and the incidence peaked during the war and post-war period at the end of the twentieth century. At that time, outbreaks with hundreds of cases and five deaths were recorded. In the first decade of the twenty-first century, the incidence decreased, and at the end of the second decade, two consecutive years without trichinellosis cases were finally registered. The analysis shows that a significantly higher incidence rate was recorded between the two political entities of BiH, the Republic of Srpska (4.97% 000) versus the Federation of BiH (0.9% 000) and that the occurrence of trichinellosis in humans in BiH is related to the presence of Trichinella spp. in animals, of a degree of biosecurity on pig farms, population's awareness of safe food, the impact of tradition and religion on eating habits, doctors' awareness of the symptomatology, and the Trichinella spp. larva detection method in muscle samples. The spread risk of trichinellosis requires meat inspection for Trichinella spp. larvae to be mandatory in BiH.

A social network approach to critical discourse studies

Abstract Viewing discourse as a social practice, one important task of critical discourse studies (CDS) is to unveil inequality, power, and ideologies through linguistic and discoursal analysis of social events, social identities, and social relations represented in oral or written texts. As such, it lends itself to social network analysis (SNA) which aims to discover relation patterns and structures among such social actors as people, organizations, and political entities. This article proposes an integration of SNA techniques into CDS and explores this possibility via an example in diachronic study on international relations represented in news reporting on China in The New York Times between 1980 and 2020 by examining subject–direct object pairs to approach the target relations between national actors. It is shown that the coupling of these two approaches effectively reveals international relation networks surrounding key national actors, based on which detailed linguistic and discoursal analysis further sheds light on the underlying ideological and socio-political factors in the news reports. Considering the fact that SNA consists of a great variety of network statistics, which can be broadly categorized into those related to the relative position of the actor in the network and those concerned with the structure of the network itself, there is vast space for the utility of SNA metrics in aiding CDS in further research.

The Influence of Social Information: A Study of Architectural Attribute from an Event Structure Analysis Perspective

Scientific and technological developments have led to gradual abstraction in architectural research and design. People no longer interpret spatial meaning simply through external forms, rather, the emphasis is put on the essence of design thinking. This change has given rise to analysis and expression methods at the level of the architectural attribute, which scientifically summarize the attributes shared by different architectural types through investigating the literature data and professional phenomena. They improve the architects’ level of awareness and provide a guiding framework for subsequent design work. However, rapid social progress and regional cultural differences make it difficult for previous methods to reflect the real-time and in-site expression of the attributes. This paper proposes a new attribute study approach based on Event Structure Analysis (ESA) in combination with social science theory. This approach provides architects with a reference for more comprehensive attribute expression by coordinating the social information at the pre-design stage. Meanwhile, with openness and operability as its technological advantages, it forms a cross-disciplinary research and exchange platform, thereby allowing public participation. The study verifies its feasibility through the structured analysis of specific social events in Beijing, discusses this interdisciplinary approach’s practical significance and positive impact at the professional and societal levels, and points out the direction for future research.

Migrating social event recommendation over microblogs

Real applications like crisis management require the real time awareness of critical situations. However, the services using traditional methods like phone calls can be easily delayed due to busy lines, transfer delays or limited communication ability in disaster areas. Existing social event analysis solutions enhanced the situation awareness of systems. Unfortunately, they cannot recognize the complex migrating social events that are first observed in social media at a specific time, place and state, but have further moved in space and time, which may affect the system comprehension. While the discussion on events appears in microblogs, their movement over different contexts is unavoidable. So far, the problem of migrating social event analysis from big media is not well investigated yet. To address this issue, we propose a novel framework to monitor and deliver the migrating events in big social media data, which fully exploits the social media information over multiple attributes and their inherent interactions among events. Specifically, we first propose a Concept TF/IDF model to capture the content that is constrained by the time and location of media without costly learning process. Then, we construct a novel Maximal User Influence Graph (MUIG) to extract the social interactions. With MUIG, the event migrations over space and time are well identified. Finally, we design efficient query strategies over Apache Spark for recommending events in real time. Extensive tests over big media are conducted to prove the high effectiveness and efficiency of our approach.

Триггеры политической мобилизации массовых протестов в социальных медиа Российской Федерации и Республики Беларусь в 2020–2021 гг.

The article presents the results of the consideration of protest mobilization triggers in the Russian Federation and the Republic of Belarus in 2020–2021. The applied research methodology is based on a hybrid strategy that combines cognitive mapping, social media analysis and event analysis. As a result, the authors reveal that the primary mobilization of protest was carried out based on a resonant event in the political sphere. To build an engaged audience, economic and social discourses were used. Protest moderators use value-influencing techniques and manipulative technologies that perform the task of scaling and forming attitudes of agreement with the ideas being promoted.

The Image of Municipalities

Purpose of the study: The aim of this study is to investigate the image of municipalities and also to determine the things that give the city a positive image of the territory. Methodology: The theoretical and methodological basis of the study is the ideas and paradigms that were developed in the works of leading domestic sociologists, cult urologists, economists, and marketers. The applied individual methods include comparative analysis, typology, classification method, questionnaire, method of analysis of social factors and events Results: The Program of socio-economic development must be amended in the form of a subprogram for the formation of a positive image of the municipality of Chekhov, since today there are no projects or programs aimed at creating a positive image of the municipality to one degree or another, its popularization and perception among the local population and among tourists. Moreover, information support of the main assets of the municipality of Chekhov (information about the advantages of the territory, photographs and advertising leaflets) in social networks, the media, on the Internet, that is, marketing of historical and cultural heritage with a priority on the work of A.P. Chekhov Applications of this study: The formation of a favorable image is of fundamental importance primarily for residents of the municipality. It affects the creation and support of social optimism among the population, trust in the authorities and confidence in the future. Novelty of the study: The image of the municipality is formed from the priority elements of its structure and a set of certain factors of development and promotion of the territory. So, the novelty of this study is to asses this image in modern life.

Multilayered Installation Design: A framework for analysis and design of complex social events, illustrated by an analysis of virtual conferencing

Humans are social animals living in societies with most of their activities occurring in social settings, characterized by multiple actors, the crossing of individual behavioral paths, interactions between participants themselves and between participants and material (or immaterial) setting components. We theorize that virtual conferences, like physical ones, have a dual-space structure where the two types of activities (content transfer and social intercourse) intertwine. Understanding what happens in such complex social events requires minutely analyzing this complex intertwined structure of components and events. This analysis is even more necessary when one wants to intervene in such settings, for example when designing supports or attempting to change behavior. Nevertheless, most methods of data collection and analysis are either centered on methodological individualism, looking at aggregates at macro or meso level, or looking in detail at only some aspects of the whole event (e.g., conversation analysis). The paper offers, while illustrating with actual data, a Multilayered Installation Design (MID) method that facilitates focus upon the various perspectives of subjects, combines them into a single framework of Installations for activity that describes the setting in a systematic and structured way, and offers directions for design or intervention. This paper (1) briefly situates the nature of the problem and some gaps in the current methodological landscape; (2) contextualizes the main theories underlying the MID method — Activity Theory and Installation Theory; (3) describes the new method per se; (4) illustrates the method on a specific case, the analysis of a conference in a virtual space; and (5, 6) lists some issues and limitations as well as future orientations. Conceptualizing issues with the help of Installation Theory informs a structured and goal-oriented approach to design that improves on the usual design thinking approach by providing a robust analytic and idea-generating framework.

Visual analysis of social events and stock market volatility in China and the USA during the pandemic.

The COVID-19 pandemic is one of the most severe infectious diseases in recent decades, and has had a significant impact on the global economy, and the stock market. Most existing studies on stock market volatility during the pandemic have been conducted from a data science perspective, with statistical analysis and mathematical models often revealing the superficial relationship between Covid and the stock market at the data level. In contrast, few studies have explored the relationship between more specialised aspects of the pandemic. Specifically, the relationship found between major social events and the stock market. In this work, a multi-source, data-based relationship analysis method is proposed, that collects historical data on significant social events and related stock data in China and the USA, to further explore the potential correlation between stock market index fluctuations and the impact of social events by analysing cross-timeline data. The results suggest and offer more evidence that social events do indeed impact equity markets, and that the indices in both China and the USA were also affected more by the epidemic in 2020 than in 2021, and these indices became less affected by the epidemic as it became the world adapted. Moreover, these relationships may also be influenced by a variety of other factors not covered in this study. This research, so far, is in its initial stage, and the methodology is not rigorous and cannot be applied as an individual tool for decision; however, it could potentially serve as a supplementary tool and provide a multi-dimensional basis for stock investors and policymakers to make decisions.

Transformation of the Far Right: What can social movement and protest event analysis tell us?

Transformation of the Far Right: What can social movement and protest event analysis tell us?

Multimodal Semantics-Based Supervised Latent Dirichlet Allocation for Event Classification

Social event classification has always been a research topic of great interest in the field of social event analysis. In existing social event classification methods, although some researchers consciously use external semantics to improve model performance, they ignore the more easily available internal semantics. In this article, we propose a multimodal supervised topic model based on semantic weighting (Sem-MMSTM), which uses two kinds of internal semantics, namely part of speech semantics and category semantics. Our Sem-MMSTM model is capable of mining and making use of the semantics of the text itself and the category semantics of multimodal supervised corpus. The experimental results show that, compared with the state-of-the-art model, our proposed Sem-MMSTM yields significant performance improvement both on the metrics of classification accuracy (ACC) and interpretability of topics (PMI) due to the introduction of effective semantic information.

KIYMETLİ TAŞLAR VE SÖMÜRGECİLİK: DİJİTAL VERİ MATERYALLERİNİN ANALİZİ ÖRNEĞİYLE

In this study, the relationship of precious stones with political / social / military and similar events in the historical process was analyzed by N-gram. The discovery of precious stones is as old as humanity, and perhaps the first material that human beings notice in nature are gemstones. These materials, which are described as gemstone / precious stones today, were already used by the local people of the geography in which they were found, mainly ornamental material, in relation to their physical and chemical properties. With the geographical discoveries that started in the 15th century, Europeans began to carry these unique materials (mainly gemstones such as diamond and jade) of the new geographies they went to, or the precious metals such as gold / silver, which they consumed by exploiting in their main continent called the old world, to the main continent. These virgin lands, which have not encountered dense human populations before, have become an important attraction for the imperialist powers because of their important natural resources and precious metals such as precious stones and gold and silver, which have heavy value at light cost in commercial terms. Afterwards, all resources (agriculture, animal, human) of these geographies, especially the natural resources, became the focus of wild exploitation. The imperialist powers, who wanted to have these resources alone, entered into a struggle with the local peoples of the geographies as well as other imperialist powers that wanted to obtain the same resources. In this struggle, the local peoples of the exploited regions suffered the most, and they were exposed to bloody conflicts, massacres, genocides, ethnic, political and social disasters. In this study, precious stones and concepts related to imperialist activities were selected as keywords and N-gram analysis was performed for a period of approximately 250 years. With this study, the N-gram analysis of political and social events (civil war, etc.) associated with the discovery / exploration / operation of mineral deposits of precious stones, and their meaningful relationships with each other were determined. Therefore, it was concluded that N-gram analyzes by selecting appropriate keywords will make a significant contribution to the literature review, which constitutes an important part of scientific studies, and that N-gram analysis will allow the realization of deeper analysis as an auxiliary research method.

Knowledge-Based Topic Model for Multi-Modal Social Event Analysis

With the accumulation of data on the Internet and progress in representation learning techniques, knowledge priors learned from a large-scale knowledge base has been increasingly used in probabilistic topic models. However, it is challenging to learn interpretable topics and a discriminative event representation based on multi-modal information. To address these issues, we propose a knowledge priors- and max-margin-based topic model for multi-modal social event analysis, called the KGE-MMSLDA, in which feature representation and knowledge priors are jointly learned. Our model has three main advantages over current methods: (1) It integrates additional knowledge from external knowledge base into a unified topic model in which the max-margin classifier, and multi-modal information are exploited to increase the number of event descriptions obtained. (2) We mined knowledge priors from over 74,000 web documents. Multi-modal data with these knowledge priors are then incorporated into the topic model to increase the number of coherent topics learned. (3) A large-scale multi-modal dataset (containing 10 events, where each event contained approximately 7,000 Flickr pages) was collected and has been released publicly for event topic mining and classification research. In comparative experiments, the proposed method outperformed state-of-the-art models on topic coherence, and obtained a classification accuracy of 85.1%.

Regression Analysis of Social Events on Values

This study uses CFPS (2010) database researching issues related to the formation of values. We use the OLS (Ordinary Least Square) method to identify the long-term effects of this group of values on those who were enrolled in school between 1986 and 1989 and aged between 15 and 22 in two dimensions, the year of birth and the highest degree. Between 1986 and 1989, two large-scale student movements took place in China. Through the use of social survey data at the individual level, the regression found that those affected by the school sentiment were more concerned with social events and less concerned with social relationships.

A survey of event analysis and mining from social multimedia

In recent years, with the popularity of mobile devices and mobile Internet, more and more social media sites are growing in an explosive way. Therefore, the social hot event will be rapidly fermented by the interaction of a large number of network users, and a large amount of multimedia data (such as texts, images and videos) will be generated. Therefore, it is important and necessary to conduct the research of multimedia social event analysis to know the evolutionary trend of social event over time automatically. This paper provides a survey and summarizes major progresses in multimedia social event analysis. We focus on four areas: (1) multimedia social event representation; (2) multimedia social event detection and tracking; (3) multimedia social event evolutionary analysis; and (4) multimedia social event topic mining.

Social multi-modal event analysis via knowledge-based weighted topic model

Along with the development of mobile Internet and social network, people’s lifestyles are also changing, and many social websites (e.g. Facebook, YouTube, and WeChat) have sprung up, which leads to the emergence of a large number of multimedia data (e.g. text, image, and video) of various events. The goal of this paper is to mine event topics efficiently from massive and unordered social media data, which is beneficial to search, browse and monitor significant social events for users or governments. In order to achieve this goal, this paper proposes a novel Knowledge-Based Multi-Modal Weighted Topic Model (KBMMWTM) for social event analysis. The proposed KBMMWTM has following advantages: (1) The proposed KBMMWTM can effectively take advantage of the multi-modality of social events jointly. (2) The proposed KBMMWTM exploits word correlation in dataset as prior knowledge to improve the performance of event topic mining. We evaluate our KBMMWTM model on a real dataset and full experiments show that our model outperforms state-of-the-art models.

Multi-modal multi-layered topic classification model for social event analysis

In this paper, we pay attention to reveal the event topics and track the evolutionary trend of social event and a novel probabilistic topic model is proposed. The Multi-modal Multi-layered Topic Classification Model (tm_MMC) for Social Event Analysis has the capacity for revealing visual and non-visual topics, by jointly modeling the textual and visual information while simultaneously learning and predicting the multi-layered category labels. In order to track the evolutionary trends of the topics online, tm_MMC uses topic intensity and heritability to incrementally build an up-to-date model. To evaluate the effectiveness of our model, we experiment using a collected data, and compare the results with those of other traditional models. The results demonstrate the effectiveness and advantages of our model against several state-of-the-art methods.

Multi-modal max-margin supervised topic model for social event analysis

In this paper, we proposed a novel multi-modal max-margin supervised topic model (MMSTM) for social event analysis by jointly learning the representation together with the classifier in a unified framework. Compared with existing methods, the proposed MMSTM model has several advantages. (1) The proposed model can utilize the classifier as the regularization term of our model to jointly learn the parameters in the generative model and max-margin classifier, and use the Gibbs sampling to learn parameters of the representation model and max-margin classifier by minimizing the expected loss function. (2) The proposed model is able to not only effectively mine the multi-modal property by jointly learning the latent topic relevance among multiple modalities for social event representation, but also exploit the supervised information by considering a discriminative max-margin classifier for event classification to boost the classification performance. (3) In order to validate the effectiveness of the proposed model, we collect a large-scale real-world dataset for social event analysis, and both qualitative and quantitative evaluation results have demonstrated the effectiveness of the proposed MMSTM.

Model IBT 3D tehnologije u sistemu dualnog obrazovanja

Multimedia tools and materials for learning have to support the programme and professional learning, i.e. they must be based on digital systems which provide simulations, problem analysis, and process analysis, along with using modern tools and technologies. By means of an integrated approach to teaching, modern-day use of computers and information-communication technologies (ICT) in education enables an overall analysis of natural and social phenomena and events. The paper describes the advantages of using modern ICT tools and applicative software in dual education on the example of the application of the integrative white-board (IWB) in the classroom. The flaws in the demonstration and simulation of ambience, environment, audio-visual experiences and multisensory interactions have been overcome owing to the development of the interactive white-board in 3D technology. The paper provides a description of a new conceptual model of using IWB in 3D technology in the classroom, i.e. the effects of its application from the perspective of dual and vocational system of education. The development of the 3D IWB technology provided a new quality of detailed graphic images, enabled an integration of and interaction with the available knowledge data bases, relevant theories and tutoring systems. The application of the 3D IWB technology turns the educational environment into a surround system, it activates simultaneously, and with a greater intensity, all senses, and directly stimulates cognitive processes, the development of various skills and muscle memory.