The ties that bind global governance: Using media-reported events to disentangle the global interorganizational network in a global pandemic

Federo, Ryan; Bustamante, Xavier

doi:10.1016/j.socnet.2022.02.012

Cited by 13 publications

(5 citation statements)

References 65 publications

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“…The Global Database of Events, Language, and Tone (GDELT) was used to extract data on INGO activities in Myanmar. The GDELT event database covers a wide range of political, economic, and social activities occurring globally, and it is the world's largest open database of human society, offering the broadest coverage, the most comprehensive content, and the highest resolution across categories [37,38]. The coverage languages include multiple language categories, with a coverage rate of 98.4%.…”

Section: Activity Datamentioning

confidence: 99%

Spatio-Temporal Evolution Characteristics and Influencing Factors of INGO Activities in Myanmar

Liu,

Zhang,

Liu

et al. 2024

IJGI

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Myanmar is among the regions with the most frequent activities of International Non-Government Organizations (INGOs). Analyzing the spatio-temporal patterns of these activities holds crucial importance for optimizing organizational coordination and enhancing governmental oversight. This study focuses on the spatio-temporal evolution characteristics and influencing factors of INGO activities in Myanmar from 2010 to 2021, utilizing spatial autocorrelation and regression analysis. The results show that the number of INGOs in Myanmar has shown a gradual slowdown in growth trends, with the number of activities exhibiting a wave-like pattern, primarily driven by spontaneous activities of INGOs. The spatial distribution of INGO activities in Myanmar is concentrated in the southern plains, with the core located in Yangon, Naypyitaw, and Loilen. Furthermore, there is significant spatial polarization in the hotspot area of INGO acticities. The hotspots followed an evolutionary path from “South Myanmar” to “North Myanmar” and then back to “South Myanmar”. INGO activities in Myanmar are more focused on the local economic level, urbanization level, medical level, education level, and total population size, providing the necessary support and services for the local society and making up for the “government malfunction” and “market malfunction”.

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Section: Activity Datamentioning

confidence: 99%

Spatio-Temporal Evolution Characteristics and Influencing Factors of INGO Activities in Myanmar

Liu,

Zhang,

Liu

et al. 2024

IJGI

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“…Due to the fact that the varying inclinations of media from different countries towards the same event play vital roles in guiding public opinion and forming differentiated impression through different countries, it is reasonable to select this variable to measure the host countries' public opinion on China. We followe ©2023 Institute of World Economics and Politics, Chinese Academy of Social Sciences Federo and Bustamante (2022) and use the NumMentions as a weight to ensure the significance and impact of various events are not overlooked. The NumMentions measures total numbers of mentions of a specific event across all reports in the GDELT database.…”

Section: Description Of Variablesmentioning

confidence: 99%

Media Inclination and Outward Foreign Direct Investment: Evidence from Chinese Firms

Hu,

Luan,

Meng

et al. 2023

China and World Economy

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Media inclinations, whether favorable or biased, play a pivotal role in shaping public opinion. Sometimes, media coverage may unintentionally foster skepticism towards foreign firms, which could create challenges for those companies when they enter new markets. Based on a panel dataset from 2005 to 2020, this is one of the first studies to investigate empirically the impact of media opinion on outward foreign direct investment (OFDI) behaviors at the firm level. The media inclination index was constructed according to the varying inclinations of media from different countries in their reporting on each event. We examined the impact of media inclination on the investment value, frequency, and number of industries. This study has revealed the following insights: (i) Positive media coverage can stimulate the investment behavior of Chinese firms. (ii) The heterogeneity analysis indicates that the promotional effect of media reporting inclination on OFDI is more significant for state‐owned firms from the investor's perspective and especially pronounced for firms in developing countries from the investee's perspective. (iii) Diplomatic visits and scientific research cooperation can amplify the positive impact of media opinions on the OFDI behaviors of Chinese firms.

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“…We also suggest that the government should make complete datasets openly available to researchers by using de-identification techniques [40]. An example of how such a database may be used can be found in an SNA study on the relational dynamics (i.e., fragmented, polycentric, and complex) of three types of international actors before and after WHO's announcement regarding the COVID-19 outbreak by using a big dataset (i.e., the Global Database of Events, Language, and Tone) to extract media-reported interactions of the actors out of trillions of data points [41].…”

Section: Remaining Concerns and Some Suggestionsmentioning

confidence: 99%

“…Figure 1. A snapshot of random-visual representation of the transmission model by gender and infection source in the first wave (red = imported, blue = local, square = male, circle = female) (55 local case numbers: 8, 9, 19, 20, 21, 22, 23, 24, 25,26,27,28,29,30, 31,32,34,35,36,37,38,41,42,43, 45, 46, 50, 92, 100, 103, 124, 130, 134, 156, 168, 169, 186, 216, 246, 247, 268, 269, 289, 299, 307, 322, 335, 336, 343, 347, 352, 365, 379, 380, 386) …”

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confidence: 99%

A Social Network Analysis of COVID-19 Transmission Models in Taiwan: Two Epidemic Waves in 2020-2021

Hsieh¹,

Hsieh²

2022

Journal of Internet Technology

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<p>The COVID-19 pandemic has made a profound global impact. As it rages on around the globe, social network researchers have been involved in exploring key factors of rapid infection and transmission. For Taiwan, it is thus worthy of exploring the differences between the transmission models of the two epidemic waves in 2020-2021 for any insight that may have been overlooked. In this study, the social network analysis is adopted for revealing any unforeseen threats of infection. In the first wave, 652 confirmed cases were reported from January 21, 2020, to November 30, 2020. In the second wave, 880 confirmed cases were reported from May 03, 2021, to May 17, 2021. The infection source attribute, i.e., local vs. imported, made the transmission models to be structured differently between the first and the second wave. In the first wave, it was found that a community outbreak could easily happen when one node got infected without knowing when and where the transmission occurred. In contrast, in the second wave, it was found that the gender attribute was more effective than the age attribute in quickly identifying the differences in the transmission models among all the confirmed cases. </p> <p> </p>

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The ties that bind global governance: Using media-reported events to disentangle the global interorganizational network in a global pandemic

Cited by 13 publications

References 65 publications

Spatio-Temporal Evolution Characteristics and Influencing Factors of INGO Activities in Myanmar

Spatio-Temporal Evolution Characteristics and Influencing Factors of INGO Activities in Myanmar

Media Inclination and Outward Foreign Direct Investment: Evidence from Chinese Firms

A Social Network Analysis of COVID-19 Transmission Models in Taiwan: Two Epidemic Waves in 2020-2021

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