scholarly journals Integrated Infodemic Surveillance System: The Case of COVID-19 in South Korea

2021 ◽  
Author(s):  
Gil-sung Park ◽  
Jintae Bae ◽  
Jong Hun Lee ◽  
Byung Yeon Yun ◽  
Byunghwee Lee ◽  
...  
Keyword(s):  
Social Media ◽  
Social Network ◽  
South Korea ◽  
Surveillance System ◽  
Data Sources ◽  
Management Policy ◽  
Multiple Sources ◽  
Related Data ◽  
Social Concerns ◽  
Different Sources

This study merges multiple COVID-19 data sources from news articles and social media to propose an integrated infodemic surveillance system (IISS) that implements infodemiology for a well-tailored epidemic management policy. IISS is an à-la-carte infodemic surveillance solution that enables users to gauge the epidemic related consensus, which compiles epidemic-related data from multiple sources and equipped with various methodological toolkits – topic modeling, Word2Vec, and social network analysis. IISS can provide reliable empirical evidence for proper policymaking. We demonstrate the heuristic utilities of IISS using empirical data from the first wave of COVID-19 in South Korea. Measuring discourse congruence allows us to gauge the distance between the discourse corpus from different sources, which can highlight consensus and conflicts in epidemic discourse. Furthermore, IISS detects discrepancies between social concerns and main actors.

Social Media Use and Participation in Dueling Protests: The Case of the 2016–2017 Presidential Corruption Scandal in South Korea

2020 ◽  
pp. 194016122094096
Author(s):  
Kiyoung Chang ◽  
Jeeyoung Park
Keyword(s):  
Social Media ◽  
Social Network ◽  
South Korea ◽  
Service Use ◽  
Media Use ◽  
Political Activism ◽  
Social Media Use ◽  
Social Network Service ◽  
Political Activities ◽  
Use Of Social Media

This study examines how citizens’ social media use may have influenced their participation in highly polarizing protests during the 2016–2017 corruption scandal in South Korea. As social media users mobilize politically by acquiring varied political information from other users, social media use created more incentives for citizens to participate in both pro- and anti-impeachment protests during the scandal. Given that social media is an important arena for political activism, participation in rival protests also influences many motivated protesters to strengthen their side’s voices online. Thus, protests may increase citizens’ political use of social media. Our empirical analysis suggests that social network service use does not influence citizens’ political activities in a unidirectional manner. We have found that social media use and participation in rival protests reciprocally influence each other.

scholarly journals A hands-on introduction to querying evolutionary relationships across multiple data sources using SPARQL

F1000Research ◽  
2019 ◽  
Vol 8 ◽  
pp. 1822 ◽  
Author(s):  
Ana Claudia Sima ◽  
Christophe Dessimoz ◽  
Kurt Stockinger ◽  
Monique Zahn-Zabal ◽  
Tarcisio Mendes de Farias
Keyword(s):  
Query Language ◽  
Data Sources ◽  
Multiple Sources ◽  
Semantic Web Technologies ◽  
Genome Database ◽  
Web Technologies ◽  
Multiple Data ◽  
Hands On ◽  
Description Framework ◽  
Different Sources

The increasing use of Semantic Web technologies in the life sciences, in particular the use of the Resource Description Framework (RDF) and the RDF query language SPARQL, opens the path for novel integrative analyses, combining information from multiple sources. However, analyzing evolutionary data in RDF is not trivial, due to the steep learning curve required to understand both the data models adopted by different RDF data sources, as well as the SPARQL query language. In this article, we provide a hands-on introduction to querying evolutionary data across multiple sources that publish orthology information in RDF, namely: The Orthologous MAtrix (OMA), the European Bioinformatics Institute (EBI) RDF platform, the Database of Orthologous Groups (OrthoDB) and the Microbial Genome Database (MBGD). We present four protocols in increasing order of complexity. In these protocols, we demonstrate through SPARQL queries how to retrieve pairwise orthologs, homologous groups, and hierarchical orthologous groups. Finally, we show how orthology information in different sources can be compared, through the use of federated SPARQL queries.

Enabling local authorities to produce short-term energy plans

2016 ◽  
Vol 27 (2) ◽  
pp. 146-166 ◽  
Author(s):  
Stella Androulaki ◽  
Haris Doukas ◽  
Vangelis Marinakis ◽  
Leandro Madrazo ◽  
Nikoletta-Zabbeta Legaki
Keyword(s):  
Decision Support ◽  
Energy Use ◽  
Energy Optimization ◽  
Data Sources ◽  
Multiple Sources ◽  
Short Term ◽  
Content Type ◽  
Related Data ◽  
Multidisciplinary Data ◽  
Term Energy

Purpose – The purpose of this paper is to identify the most appropriate multidisciplinary data sources related with energy optimization decision support as well as the related methodologies, tools and techniques for data capturing and processing for each of them. Design/methodology/approach – A review is conducted on the state-of-play of decision support systems for energy optimization, focussing on the municipal sector, followed by an identification of the most appropriate multidisciplinary data sources related with energy optimization decision support. An innovative methodology is outlined to integrate semantically modeled data from multiple sources, to assist city authorities in energy management. Findings – City authorities need to lead relevant actions toward energy-efficient neighborhoods. Although there are more and more energy and other related data available at the city level, there are no established methods and tools integrating and analyzing them in a smart way, with the purpose to support the decision-making process on energy use optimization. Originality/value – A novel multidimensional approach is proposed, using semantic technologies to integrate data from multiple sources, to assist city authorities to produce short-term energy plans in an integrated, transparent and comprehensive way.

Reconstruction of 3D Strata Model Based on Data from Multiple Sources

2014 ◽  
Vol 602-605 ◽  
pp. 3228-3231
Author(s):  
Pan Li ◽  
Liang Hu
Keyword(s):  
Delaunay Triangulation ◽  
3D Modelling ◽  
Data Sources ◽  
Multiple Sources ◽  
Contour Maps ◽  
Modelling Method ◽  
Realistic Result ◽  
Using Data ◽  
Different Sources ◽  
Modelling Process

Given the multiple-sources feature of geological interface data, in this paper we propose a universal 3D modelling method using data forms presented as dirllhole diagrams, geologic sections, and vectorized contour maps. In our strategy, data from different sources are all treated as discrete property points, upon which cubic interpolation interpolation is performed to make a denser grid. The final step is accomplished through constrained Delaunay triangulation of the top and bottom grids and boundaries to generate the strata model through triangular strips. Our method merges all kinds of data sources available into one single modelling process, thus the most realistic result is guaranteed.

scholarly journals Strengthening the Monitoring of Violations against Journalists through an Events-Based Methodology

2020 ◽  
Vol 8 (1) ◽  
pp. 89-100 ◽  
Author(s):  
Jackie Harrison ◽  
Diana Maynard ◽  
Sara Torsner
Keyword(s):  
Sustainable Development ◽  
Full Range ◽  
Data Sources ◽  
Depth Information ◽  
Multiple Sources ◽  
Sustainable Development Goal ◽  
Development Goal ◽  
Communicative Functions ◽  
Extensive Collection ◽  
Different Sources

Sustainable Development Goal (SDG) indicator 16.10.1 proposes an important monitoring agenda for the global recording of a range of violations against journalists as a means to prevent attacks on the communicative functions of journalism. However, the need for extensive collection of data on violations against journalists raises a number of methodological challenges. Our research shows the following issues must be addressed: the lack of conceptual consistency; the lack of methodological transparency; the need for sophisticated data categorisation and disaggregation to enable data to be merged from different sources; the need to establish links to understand causal and temporal relations between people and events; and the need to explore and utilize previously untapped data sources. If we are to strengthen the monitoring of SDG 16.10.1, we propose to develop a robust and reliable events-based methodology and a set of tools which can facilitate the monitoring of the full range of proposed 16.10.1 categories of violations, reconcile data from multiple sources in order to adhere to the established 16.10.1 category definitions, and to further disaggregate the proposed 16.10.1 categories to provide more in-depth information on each instance of a violations. This, we argue, will ultimately contribute towards better understanding of the contextual circumstances and processes producing aggressions against journalists.

Research in Social Media: Data Sources and Methodologies

2017 ◽  
Vol 33 (1) ◽  
pp. 1-28 ◽  
Author(s):  
Roger S. Debreceny ◽  
Tawei Wang ◽  
Mi (Jamie) Zhou
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Sites ◽  
Data Sources ◽  
Dynamic Nature ◽  
Social Media Data ◽  
Corporate Announcements ◽  
Use Of Social Media ◽  
Media Data ◽  
Extract Information

ABSTRACT This paper examines both the opportunities and limitations in the use of social media for accounting research. Given the dynamic nature of social media and the richness of the context, there are opportunities for researchers to directly observe communication and information exchanges, typically within the context of an observable social network. The paper provides an overview of the characteristics of four commonly used social network sites (SNSs): Facebook, Twitter, LinkedIn, and StockTwits. The data collection details, opportunities, and limitations are set out. The paper also provides illustrative examples of codes that a researcher might employ to extract information from the SNSs. To provide a comparison of accounting-relevant interactions, the paper measures the extent of posts on StockTwits, Twitter, and Facebook for a random sample of corporate announcements.

scholarly journals A CYBERCULTURE STUDY: K-POP AND THE NEW MEDIA - BTS AND TWITTER

2021 ◽  
Vol 6 (6) ◽  
Author(s):  
Luís Cardoso ◽  
Matilde Castanho
Keyword(s):  
Social Media ◽  
Social Network ◽  
New Media ◽  
South Korea ◽  
Music Industry ◽  
Anglo Saxon ◽  
Cultural Phenomenon ◽  
The Social ◽  
New Form

This paper intends to describe, analyze, and reflect on the presence of K-Pop in the cybernetic environment, as a cultural and artistic manifestation of the XXI century, as well as to study and evaluate the participation of the band BTS (and its fan community) in the social network Twitter, looking for an understanding of its identity and contribution to the cyberculture universe. The importance of “Korean Pop” for the global music industry is, in present times, an undeniable fact, because of the success of several artists and groups of Korean heritage and/or managed by labels from South Korea that have been occupying the top places in charts previously dominated by Anglo-Saxon performers. The band Bangtan Sonyeondan, known worldwide as BTS, formed by Big Hit Entertainment in 2010, is pointed by the critics and specialists as one of the most successful and mediatic groups of the last years. The comparisons between the Beatlemania from the 60s and the behaviour of its fan base (self-proclaimed Army) are quite common. In this context, we intend to study this cultural phenomenon as a new form of culture and interaction between artists and admirers, using social media and new socialization techniques created and adapted to cyberspace. <p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0875/a.php" alt="Hit counter" /></p>

Discovering related data at scale

2021 ◽  
Vol 14 (8) ◽  
pp. 1392-1400
Author(s):  
Sagar Bharadwaj ◽  
Praveen Gupta ◽  
Ranjita Bhagwan ◽  
Saikat Guha
Keyword(s):  
Machine Learning ◽  
Data Streams ◽  
State Of The Art ◽  
Ground Truth ◽  
Data Sources ◽  
Multiple Sources ◽  
Related Data ◽  
Scale Data ◽  
Require Data ◽  
Relevance Model

Analysts frequently require data from multiple sources for their tasks, but finding these sources is challenging in exabyte-scale data lakes. In this paper, we address this problem for our enterprise's data lake by using machine-learning to identify related data sources. Leveraging queries made to the data lake over a month, we build a relevance model that determines whether two columns across two data streams are related or not. We then use the model to find relations at scale across tens of millions of column-pairs and thereafter construct a data relationship graph in a scalable fashion, processing a data lake that has 4.5 Petabytes of data in approximately 80 minutes. Using manually labeled datasets as ground-truth, we show that our techniques show improvements of at least 23% when compared to state-of-the-art methods.

Emotive Trending And Tracking of Tweets

2017 ◽  
Vol 7 (11) ◽  
pp. 25
Author(s):  
Sanjay Chhataru Gupta
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Social Network ◽  
The Social ◽  
The World ◽  
Complex Events

Popularity of the social media and the amount of importance given by an individual to social media has significantly increased in last few years. As more and more people become part of the social networks like Twitter, Facebook, information which flows through the social network, can potentially give us good understanding about what is happening around in our locality, state, nation or even in the world. The conceptual motive behind the project is to develop a system which analyses about a topic searched on Twitter. It is designed to assist Information Analysts in understanding and exploring complex events as they unfold in the world. The system tracks changes in emotions over events, signalling possible flashpoints or abatement. For each trending topic, the system also shows a sentiment graph showing how positive and negative sentiments are trending as the topic is getting trended.

Opportunities for Qualitative Analysis of Social Media Platforms in Dietetic Research and Practice

2020 ◽  
pp. 1-5
Author(s):  
Meghan Lynch ◽  
Irena Knezevic ◽  
Kennedy Laborde Ryan
Keyword(s):  
Social Media ◽  
Low Cost ◽  
Online News ◽  
News Article ◽  
Discussion Forums ◽  
Research And Practice ◽  
The Public ◽  
Related Data ◽  
Social Media Platforms ◽  
Article Comment

To date, most qualitative knowledge about individual eating patterns and the food environment has been derived from traditional data collection methods, such as interviews, focus groups, and observations. However, there currently exists a large source of nutrition-related data in social media discussions that have the potential to provide opportunities to improve dietetic research and practice. Qualitative social media discussion analysis offers a new tool for dietetic researchers and practitioners to gather insights into how the public discusses various nutrition-related topics. We first consider how social media discussion data come with significant advantages including low-cost access to timely ways to gather insights from the public, while also cautioning that social media data have limitations (e.g., difficulty verifying demographic information). We then outline 3 types of social media discussion platforms in particular: (i) online news article comment sections, (ii) food and nutrition blogs, and (iii) discussion forums. We discuss how each different type of social media offers unique insights and provide a specific example from our own research using each platform. We contend that social media discussions can contribute positively to dietetic research and practice.

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