Bibliometric mapping of the trends and contributions of scientific publications to risk and crisis communication regarding South America

Figures & data

Figure 1. Main approaches and authors linked to communicating risks. Sources of information (Heath & O’Hair, 2020; Lundgren & McMakin, 2018).

Table 1. Statistics on extreme natural events and disasters in South America from 2016 to 2021. Source (CEPAL, 2022)

Hazards	Events	Human loses	Affected people
Related to climate change
Floods	125	1,018	6,530,317
Wet mass movement	12	511	49,188
Storms	8	37	281,250
Fires	7	26	9,577
Droughts	5	8	700,032
Geophysicists
Earthquakes	11	1,357	418,820
Volcanic eruptions	3	NA	166,306
Dry mass movement	1	NA	18,685
Total	172	2,957	8,174,175

Table 2. Explanation of the independent variables

Variables	Explanations	Source
Disaster characteristics	Number of human deaths reported	(CEPAL, 2022)
Number of people affected	Number of humans affected reported	(CEPAL, 2022)
Number of confirmed cases (COVID-19)	Number of humans confirmed with COVID-19	(ECDC, 2022)
Economic development GDP per capita (Current US$)	Gross domestic product divided by midyear population	(World-Bank, 2022)
International tourism, number of arrivals	Tourists who travel to a country other than their usual residence.	(World-Bank, 2022)
Net trade in goods and services (BoP, current US$)	Net trade in goods and services is calculated by balancing imports and exports of goods and services.	(World-Bank, 2022)

Figure 2. Publications published and cited on South America in WoS as of December 2, 2021.

Table 3. Percentage of scientific publications (N = 330), times cited, the average of citations per item, and H-index related to risk and crisis communication regarding South America

ID	Country Name*	% of publications	Times cited	Average per item	H-index
BR	Brazil	50.61	1029	6.16	18
CL	Chile	16.06	441	8.32	12
AR	Argentina	11.82	248	6.36	8
CO	Colombia	11.21	158	4.27	7
EC	Ecuador	9.39	135	4.35	5
PE	Peru	7.58	131	5.24	6
VE	Venezuela	2.73	80	8.89	2
TT	Trinidad and Tobago	1.52	32	6.4	2
BO	Bolivia	1.21	55	13.75	2
UY	Uruguay	1.21	29	7.25	3
PY	Paraguay	0.61	90	45	2
GY	Guyana	0.61	18	9	1
SR	Surinam	0.30	20	20	1

*No publications related to French Guiana were detected.

Table 4. Percentage of publications by hazard type. The hazards type was examined using the keyword co-occurrence map (section 3.2): diseases = covid-19, disease, pandemic; human activities = agricultural, mining, industry; climate change = climate change, climate change communication; and natural extremes = volcanoes, earthquake, flood

Extreme Events	Percentage of publications	Times cited	Average of citations per item	H-Index
Diseases	30.91%	704	6.9	13
Human activities	8.48%	338	12.07	9
Climate change	7.58%	223	8.92	7
Natural extremes	4.55%	72	4.87	5

Figure 3. Keyword co-occurrence network constructed from 83 words with a minimum frequency of five words.

Table 5. Factors for risk communication in vulnerable areas (red cluster)

ID	Explanation	Publications (%)	Average per item	H-index
1.1	Risk communication and risk perception management (Zinn, 2021) KW: risks, risk communication, perception, risk perception	23.24	10.76	16
1.2	Empowerment of risk communication management instruments (Viteri & Takahashi, 2020) KW: cooperation, framework, governance, knowledge, management, model, networks, system	22.18	9.1	13
1.3	Recognition of vulnerability to different threats (Coates, 2021) KW: vulnerability, vulnerable zones, environmental	11.97	13.41	10
1.4	Management of the expected goals of risk communication (Vallejos Romero, 2012). KW: behavior, challenges, disaster risk reduction, resilience, trust	9.86	10.93	11

Table 6. Factors for health and crisis communication (green cluster)

ID	Explanation	Publications (%)	Average per item	H-index
2.1	Communication and information (Villela & Almeida, 2013) KW: communication, information	38.38	6.74	13
2.2	Health communication and prevention management (Cezar-Vaz et al., 2015) KW: prevention, health, health communication	17.61	5.55	10
2.3	Articulation of the media and journalism(Miranda Costa, 2016) KW: media, journalism	15.14	4.26	6
2.4	The use of technology for communication (Tejedor et al., 2020) KW: internet, web, social network, mobile application, technology	12.68	5.5	6
2.5	Managing the negative effects of misinformation (Mullo López et al., 2021) KW: fake news, ethics	4.58	3.85	4
2.6	Crisis communication (Gomez-Zapata et al., 2021) KW: crisis communication	3.17	1.89	2

Table 7. Factors associated with the communication of human and environmental exposure to pollutants (blue cluster)

ID	Explanation	Publications (%)	Average per item	H-index
3.1	Integration of scientific communication in risk policy (Dada et al., 2021) KW: science communication, policy	5.99	6.24	5
3.2	Recognition of human and environmental exposure to contaminants (Cubillas-Tejeda et al., 2018) KW: exposure, pesticides, pollution	5.28	16.73	7
3.3	Articulation of the health system to the risk management system (Pingel et al., 2021) KW: health system	5.28	7.4	6
3.4	Monitoring of spaces subject to contamination (Cama et al., 2013) KW: monitoring, wireless, environment	4.58	9.08	6
3.5	The importance of leadership in R&CM (Coates, 2021) KW: leadership	2.46	8.14	4
3.6	Management of children’s perception of risks and disasters (Ottenbros et al., 2019) KW: children	2.11	18	3

Table 8. Management of continuity and communication quality (yellow cluster)

ID	Explanation	Publications (%)	Average per item	H-index
4.1	Continuity of information and communication technologies (Loza et al., 2021) KW: information and communication technologies, resources	10.21	2.62	6
4.2	The right to education during crisis events (Pascual et al., 2016) KW: education, school, teaching	8.45	5.04	5
4.3	Political environment and right to information (Ribeiro et al., 2020) KW: rights, political	5.28	3.93	4
4.4	Consideration of cultural diversity and social vulnerability (Zinn, 2021) KW: social, social minorities	4.58	4.77	4
4.5	Digital communication (Tejedor et al., 2020) KW: digital communication	3.87	6.55	2
4.6	Disaster impact communication (Miranda Costa, 2017) KW: impact	2.82	6.88	4

Table 9. Enhancers for environmental and climate change communication (purple cluster)

ID	Explanation	Publications (%)	Average per item	H-index
5.1	Management of coverage, framing and discourse (Orlove et al., 2019) KW: coverage, framing, discourse	6.69	5.11	5
5.2	Recognition of the transdisciplinary nature of R&CM (Wilmshurst, 2018) KW: sciences	6.69	9.5	8
5.3	Management of the quality and legitimacy of communication (Kouloukoui et al., 2019) KW: strategies, adaptation, legitimacy	6.34	9.28	7
5.4	Management of community participation in R&CM (Pascual et al., 2016) KW: community	3.87	7.64	5
5.5	Environmental communication (Castello, 2021) KW: environmental communication	2.46	3	4
5.6	Climate change communication (Paerregaard, 2020) KW: climate change communication	1.76	6.6	2

Figure 4. Co-citation map. Minimum of eight citations of an author.

Figure 5. Cross-analysis between the most cited authors and communication factors (see section 3.2). Only the most significant relationships were represented.

Figure 6. Network visualization map of inter-country cooperation for communication research. The map was created with VOSviewer software version 1.6.16. The minimum number of documents in a country was 5.

Figure 7. Relationship between total publications and H-index of the countries that have published through cooperation networks. The size of the circles indicates the average number of citations per article.

Figure 8. Map of co-authorship by authors with two or more publications (48 authors out of a total of 1,189). The size of the circle refers to the number of publications.

Figure 9. Classification of publications on R&CC according to the research area proposed by web of science.

Table 10. Authors with three or more publications

Author	Publications	Times cited	Average citations per publication	H-index
Ochoa	6	114	19	4
Di Giulio/Figueiredo	4	21	5.25	3
Bonow/Cezar-Vaz	4	25	6.25	3
Santos	3	32	10.67	3
Dos Anjos	3	15	5	3
Massarani	3	5	1.67	1

Figure 10. Principal component analysis of the factors of risk and crisis communication regarding South America.

Table 11. Determinants of communication research in the face of risks and crises

Variables	Overall model	Discount model	CoDA model
(Intercept)			1.505e + 00***(.000)
Disaster characteristics
Number of people killed		4.870e-01***(.000)
Number of people affected		−3.702e-05*(.039)	−2.764e-06***(.003)
Number of confirmed cases (COVID-19)	1.742E–05***(.000)
Economic development
International tourism, number of arrivals		5.107e-06***(.000)	−1.475e-07**(.009)
Net trade in goods and services	.0011*(.023)
GDP per capita			8.310e-05**(.008)
Multiple R^2	.9593	.9604	.8037
Adjusted R-squared	.9519	.9485	.7383
F	129.6	80.8	12.29
N	13	13	13
Akaike Information Criteria	104.07	99.36	17.23

***P < .001 **P < 0.01 *P < 0.05 ‘’. P < 0.1.

Figure 11. Compositional estimation of the determinants of R&CC.

Figure 12. The value of scientific research in the context of R&CC systems.

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Data availability statement

The paper is based on the Web of Sciences (WoS) online scientific information service.