=Paper=
{{Paper
|id=Vol-3353/paper12
|storemode=property
|title=Disinformation in Social Networks: A Systematic Review on Fake News in Times of Pandemic
|pdfUrl=https://ceur-ws.org/Vol-3353/paper12.pdf
|volume=Vol-3353
|authors=Paola Meza-Gómez,José Enrique García-Tejada,Jorge Mamani-Calcina,Cesar Gonzalo Vera-Vásquez,Nelly Mamani-Berrios,Miguel Angel Ortiz-Esparza
|dblpUrl=https://dblp.org/rec/conf/citie/Meza-GomezGMVME22
}}
==Disinformation in Social Networks: A Systematic Review on Fake News in Times of Pandemic==
https://ceur-ws.org/Vol-3353/paper12.pdf
Disinformation in Social Networks: A Systematic Review on
Fake News in Times of Pandemic.
Paola Meza-Gómez 1, José Enrique García-Tejada 2, Jorge Mamani-Calcina 3, Cesar Gonzalo
Vera-Vasquez 4, Nelly Mamani-Berrios 2 and Miguel Angel Ortiz-Esparza 5*
1
Universidad Católica de Santa María, Arequipa, Perú.
2
Universidad Nacional de San Agustín, Arequipa, Perú.
3
Universidad Tecnológica del Perú, Arequipa, Perú.
4
Universidad Continental, Arequipa, Perú.
5
Centro de Investigación en Matemáticas.
Abstract
The use of social media, low literacy, fast information sharing and preprint services are
identified as the main causes of the infodemic [4] and among its consequences we find that it
can promote public health risk behaviors globally. The results of
Fake news represents a threat to societies in the context of the pandemic. The aim of this article
is to review existing research on fake news in the last 2 years, discussing the characteristics of
infodemics, media/digital literacy and its impact on society, as well as highlighting
mechanisms to detect and curb fake news on covid-19 in social networks. Thirty articles were
analyzed and selected from 1354 open access articles on this subject. The conclusion was that
knowledge of fake news should be taken note of due to the harmful effects on society,
considering the informational contexts (epistemic, normative and emotional), together with
media literacy to increase trust and emphasize public health messages with emotionally
relevant and scientifically based content, in order to continue conducting research that allows
a 100% effective recognition and elimination of untruthful information on social networks.
Keywords 1
Covid-19, disinformation, fake news, rumors, social networks, digital literacy, infodemics,
deep network detection.
1. Introduction
The development of the internet as we know it resulted in multiple benefits for society, opportunities
to share convictions and opinions. Unfortunately, it represents a place for conspiracy theories,
disinformation and dissemination of untruthful information. In the first weeks of 2020, when the
coronavirus outbreak was centered in China, few people had been diagnosedin other countries. At this
time, the coverage of the epidemic in international media was small.
However, once it became clear that the virus was expanding, media coverage increased and with it
the spread of panic.
The dissemination and creation of fake news through social networks represents a danger to society,
the economic system and democracy [1]. The circulation of fake news during a health crisis is often
motivated by the desire to suppress or distort key official messages for recovery. Almost half of the
health content posted on social networks contains misinformation since, one of the most salient
characteristics of fake news is that it has a narrative that has a detrimental impact [2] with fear or
mistrust, which can generate serious problems in the short, medium and long terms [3].
CITIE 2022: International Congress on Trends in Educational Innovation, November 8-10, 2022, Arequipa, Perú
*Corresponding author.
EMAIL: pmezag@ucsm.edu.pe (P. Meza-Gómez); jgarciate@unsa.edu.pe (J. García-Tejada); e16187@utp.edu.pe (J. Mamani-Calcina);
cverav@continental.edu.pe (C. Vera-Vasquez); nmamanib@unsa.edu.pe (N. Mamani-Berrios); miguel.ortiz@cimat.mx (M. Ortiz-Esparza)
ORCID: 0000-0001-6317-0910 (P. Meza-Gómez); 0000-0001-5990-4897 (J. García-Tejada); 0000-0001-6633-2102 (J. Mamani-Calcina);
0000-0003-4168-5117 (C. Vera-Vasquez); 0000-0003-0571-8321 (N. Mamani-Berrios); 0000-0001-8762-5780 (M. Ortiz-Esparza).
©️ 2022 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
Kabha's research [11] include several impacts from the dissemination of misinformation to the
misuse of drugs to cure the disease. Health misinformation about vaccines were also verycommon
(43%) [5]. According to the review of Gabarron y Win [6], of the 22 investigations, 11 did not
categorize the type of COVID-19- related misinformation, 9 described specific misinformation myths,
and 2 reported sarcasm or humor related to COVID-19. But, susceptibility to interact with fake news is
independent of the individual educational level of each study subject.
Major media platforms contain mainly fake news and during the current pandemic generated many
concerns regarding public health and communication. According to studies by Alí [1], Córdova [3] and
Rocha [7], there is a strong significant correlation between social media platforms (Facebook, YouTube
and Twitter) and fake news.
The spread of rumors, especially about government performance, on social media is clearly of
concern [8], and artificial intelligence, natural language processing (NLP) and deep learning techniques
are currently being applied to detect fake news before its spread via social networks on covid-19.
However, in reviews done so far, the benefits of media and digital literacy, related to automated fake
news detection practices, are not explained in detail. Therefore, the objective of this review is to conduct
a review in relation to fake news, discussing the characteristics of the infodemic, media/digital literacy
and the impact of this for society, as well as mechanisms to detect and stop fake news about covid-19
in social networks.
2. Methodology
For the reporting of this systematic review, the PRISMA (Preferred Reporting Items for Systematic
Reviews and Meta- Analyses) 2020 standards are applied to identify eligibility criteria, sources of
information, search strategy, selection process, data collection process, and data list.
3. Search Equation Databases Consulted:
For the present case, 3 relevant databases were chosen for the study of the identification of fake
news. One digital library (IEEE Xplore) and two documentary databases (Scopus and Web of Science)
were selected. All index impact articles. And while all of them show relevant results in the field of
Computer Science, important for the detection of fake news; Scopus and WoS also show relevant
information for social sciences.
SEARCH STRING
(("Fake News" OR "Media misinformation" OR Misinformation OR Rumors OR Disinformation)
AND ("Social Media" OR "Social Network" OR "Online News" OR Twitter OR Facebook OR
Whatsapp) AND ("COVID-19" OR covid OR coronavirus OR quarantine OR pandemic)))
INCLUSION AND EXCLUSION CRITERIA
INCLUSION CRITERIA EXCLUSION CRITERIA
Articles published in scientific journals The text of the article is not availablefor reading.
between January 2020 and January2022.
Publications indexed in the databases wehave The article is written in a languageother than English or
established. Spanish.
Articles that do not develop educational research related
to information literacy, media literacy, digital literacy,
The text of the article must be availablefor reading. data literacy or newsrelated to COVID-19 in social
networks.
The article is written in Spanish orEnglish. Articles whose purpose is thepresentation of
monographs.
Articles with the keywords "fake news",
Reviews, theses, conferences, andeditorials
"disinformation" or "misinformation" or"COVID-19".
Proposals that will analyze and employmechanisms Repeated documents, documents written in a language
to detect and/or stop fake news in social networks. other than English or Spanish, inaccessible documents,
and documents publishedbefore 2020.
4. Prism Diagram
Figure 1: Prism Diagram
Table 1
Socio-demographic profile of residents
SOCIODEMOGRAPHIC VARIABLES N° %
20–30 years 4 13.3
31–40 years old 5 16.7
Age
41–50 years 6 20.0
51 and over 15 50.0
Single 8 26.7
Married 9 30.0
Marital Status
Cohabiting 9 30.0
Divorced 3 10.0
Widowed 1 3.3
No education 2 6.7
Completed elementary school 4 13.3
Incomplete Elementary 8 26.7
Grade of Education
High school completed 8 26.7
Incomplete High school 4 13.3
Superior - Technical 4 13.3
2–3 members 13 43.3
Number of family members 4–5 members 11 36.7
6 or more members 6 20.0
< SMV 27 90.0
Income from Crafts = SMV 2 6.7
> SMV 1 3.3
It was evaluated whether the artisan women are complying with the general pre-ven-tive measures
imposed by the Peruvian state, which are as follows: carrying out clean-ing and disinfecting process on
surroundings, furniture, tools, and equipment among other inert surfaces to ensure they are free of
COVID-19; ensuring the quanti-ty and lo-cation of hand washing points (water, liquid soap or gel) and
alcohol for the artisan's use; implementing the correct use of double surgical masks or a KN 95 and
respecting the social distance of at least 1 meter.
The results obtained show that 93.3% of artisan women have been vaccinated against COVID-19,
which is the most effective prevention measure worldwide (see Table 2).
In terms of compliance with the general preventive measures, 70% of the artisan women do not
comply or are at a beginner level with the health protocols and 30% of the artisan women are in the
process, meaning that in some cases they use alcohol when in contact with another person, they clean
and disinfect their work tools and use a surgical mask.
Table 2
General preventive measures
HEALTH SITUATION-COVID 19 N° %
Yes 28 93.3
COVID 19 Vaccine
No 2 6.7
Level of Compliance with Non-compliant/ Beginning 21 70.0
General Preventive In Process 9 30.0
Measures Total 30 100.0
Concerning compliance with COVID-19 preventive measures in the production pro-cess and the
sale of artisan work, three stages have been identified: Before the activity–artisan work production
process (stage 1); at the sale of artisan work in workshops, stalls, or artisan stores (stage 2) and after
the artisan activity (stage 3), as shown in Table 3.
In compliance with stage 1, 70% of the artisan women do not comply or are in the pro-cess of
beginning to comply with the preventive measures, with the lowest indicators being when more than
two artisans meet to produce their work, they do not keep social distance and do not use double surgical
masks or a KN 95 with 80% and 83.3%, respectively.
Concerning compliance with stage 2—regarding the sale of artisan work in the work-shop, stall, or
store—100% of the artisan women do not comply with the prevention measures, for tourism revival
and are not prepared to serve the public. Only 16.7% of the artisan women have installed or use a hand
sanitizing point at the entrance of the workshop, stall, or store. A hand disinfection point has been
installed or used at the entrance of the workshop, stall, or craft store by 7% of artisan women; only
3.3% use electronic payment methods or digital wallets as most of them are afraid of electronic
transactions and 100% have not placed signs that promote care and measures to pre-vent COVID 19.
In compliance with stage 3, 76.7% of the artisan women do not comply or are in the process of
beginning to comply with the preventive measures after carrying out their activities; only 23.3% store
raw materials and consumables in the storage area, discard the containers (bags, paper, etc.) and
disinfect the area; 83.3% of the artisan women wash and disinfect their hands at the end of the operation.
Table 3
Preventive measures in the production and sales process.
PREVENTIVE MEASURES IN THE PRODUCTION AND
COMPLIANCE
SALES PROCESS
Non-
Freq Perce Compliant Compliance /
In Process
QUESTIONS uenc ntag / Achieved
y e Beginning
N° % N° % N° %
Cleaning and disinfection Yes 10 33.3
of raw materials, supplies,
tools, and equipment at No 20 66.7
the beginning of the
workday. Total 30 100
Yes 12 40
Washing and disinfection
of hands when starting the No 18 60
production of their work.
Total 30 100
Stage
When more than two Yes 6 20 21 70 4 13.3 5 16.7
1
craftswomen come
together to produce their No 24 80
work, they ensure social
distancing (1 meter). Total 30 100
When more than two Yes 5 16.7
craftswomen come
together to produce their No 25 83.3
products, they use double
surgical masks or a KN Total 30 100
95.
Install and use a hand Yes 5 16.7
sanitizing station at the
No 25 83.3
entrance of the workshop,
booth, or artisan store. Total 30 100
Places signage to promote
Stage
social distancing at the No 30 100 30 100 0 0 0 0
2
point of sale
Yes 1 3.3
Use electronic means of
payment or a digital wallet No 29 96.7
for transactions.
Total 30 100
Store raw materials and Yes 7 23.3
supplies in the storage
area, discard packaging No 23 76.7
(bags, paper, etc.), and
Stage disinfect. Total 30 100
23 76.7 2 6.7 5 16.7
3 Yes 5 16.7
At the end of the
operation, hands are No 25 83.3
washed and disinfected.
Total 30 100
5. Results
This pandemic generated by covid-19 is an important event that brings disinformation generating
two basic problems for public safety: Propagation of misinformation and also the so-called infodemic.
Disinformation is false or incorrect information in overabundance that makes it difficult for people to
find reliable sources when they need them according to WHO [9]. Covid-19 was declared a pandemic
by WHO on March 11, 2020 and before that the disinformation in social networks about it was already
causing damage worldwide, so the threat of the infodemic was announced in February 2020 at the
Munich security conference.
Marín (2021) [10], explains that there are three types of informative context: weak epistemic
(information is not always shared to inform), strong normative (prescriptive or evaluative statements)
and strong emotional (emotional manipulation in the news), in each one, but especially the strong
emotional context, social networks play a fundamental role in exploring people's behaviors. In a crisis
context the amount of information overwhelms the public generating attention fatigue that affects
health-related behaviors and emotional responses such as fear, sadness, nervousness, confusion,
amusement, anxiety that surface distrust and competition between information sources reducing the
dissemination of useful health information generating stress and discouragement, affecting the
emotional health of the recipients, there being a significant positive statistical correlation between social
networks and the spread of panic about COVID-19. This could be influenced by demographic and
generational characteristics such as age and the context in which the people receiving the information
analyze it. For example, the study by Soleymani, et al (2021) [12] (n=24), explained that everyone had
a specific attitude towards the crisis, among these, many people developed the illusion of being infected
by the coronavirus when hearing news about patients and, especially, their deaths. In addition,
emotional language can help the success of, for example: (vaccination campaigns, distribution of
information, and decrease in the spread of fake news). Therefore, the researchers agree that education
could increase trust and emphasize public health messages with emotionally relevant and science-based
content. It was possible to identify that the social network Twitter predominated among the chosen
documents appearing in 6 articles [13]; [14]; [15]; [16]; [17], followed by Facebook with
participation in 2 articles [18]; [19]; while WhatsApp, Youtube, Instagram, Weibo and Tiktok
appeared in only one article [20]; [21]; [22]; [23]; [24].
The discussion on social networks has been affected, dramatically increasing topics about COVID
or related topics. The most recurrent topic concerning coronavirus on YouTube and Tiktok was
prevention. Due to the crisis, economy was also another quite searched topic as is the case in India [13],
and that of Twitter where: "company", "stocks", "economy/economic", "Nasdaq", "wall street" were
the most searched terms; but not that of Tiktok where it was unpopular[17]. Disinformation about
coronavirus was also quite widespread. In Tiktok it was identified that 27% of the videos had incorrect
information about COVID-19 [22]. On twitter, the following were used: 'fake news', 'circulating on
social', 'socialnetwork', 'social media' and 'circulating' for misinformation; 'world health organization'
'ministry of health' 'media briefing' for fabricated information; and 'latest information' and 'situation
report' for partially false information [22]. In Northern, Western and Southern Europe, words associated
with disinformation such as the effects of technological advances were used (5G) In Spanish words like
'plandemic' or 'coronatimo' were widely used to discredit the coronavirus [15]. And on twitter in English
words like #vaccineskill and #vaccinesharm to discredit vaccines. [25] On the other hand, the sources
most used by people to get information about the pandemic were social networks, both in studies done
in Spain, Palestine and Iran. Within them it was found that both YouTube and Twitter the most prevalent
sources of information about COVID were official news media [21], [26]. In comparison on both
Instagram and Tiktok where the highest amount were produced by public accounts; 67.1% [23] and
96% [22] of total posts respectively. These accounts are likely to use scientific expertise strategically
to reinforce one's own pre- existing evaluative opinions [10] and contrary to network consumption,
trustworthiness in news shared on these media is quite reduced in generation Z. In Iran likewise
individuals stated that pieces of information are disseminated anonymously and cannot be easily trusted,
thus stating that it is necessary to validate such information [12], and traditional, alternative media and
social networks themselves are the sources of authority attributed in 84.3% of cases. [15]
(Soleymani et al., 2021) [12], describes that media literacy of people decreases the
counterproductive impact of disinformation and the spread of false news, a tool that improves its
effectiveness when coordinated with the media, educators and governmental institutions [27]. Moore
& Hancock [28] present media literacy as an instrument of well-being for older adults, since decreasing
their relationship with fake news favors their media learning, allowing them to avoid possible attacks
on their emotional stability and interaction in social networks. Media literacy maintains the same
objective, to be seen as a tool to fight against fake news and the resilient role of education, as it seeks
to enable people to make correct use of information resources and avoid disinformation [12].
Currently, studies are applying artificial intelligence and natural language processing (NLP)
techniques to detect fake news before it spreads via social networks and in April 2020, the Facebook
platform managed to eliminate approximately fifty million publications related to COVID-19, as these
were classified as fake news through the application of NLP methods based on automated learning. As
well as conducting surveys to collect responses, give criteria for credibility, conformability, reliability
and transferability of information. However, one thing that stands out is the fine line between the task
of deleting accounts, suspending users or removing messages, and maintaining freedom of expression,
which means that the design of the rules of use is always one step behind the conversation on social
networks. Therefore, interventions by the relevant authorities can exploit the positive power of social
networks to distribute accurate information from primary and reliable sources.
The findings indicate that most of the users of social networks accept false information as they feel
insufficient knowledge and irrelevant experience in the subjects proposed in the networks. The most
effective methods and materials with respect to differentiating fake news from real news [29], the
optimal deep learning performance classifiers are, GRU (Closed Recurrent Units), LSTM (Long Short-
Term Memory), RNN (Recurrent Neural Network, and offer results of discarding fake news in 86.12%.
on the other hand, methods used by a large part of researchers in this regard is verification by PLS-SEM
analysis technique, rumor refutation and through a crawler.
6. Discussion
This pandemic generated by covid-19 is an important event that brings disinformation generating
basic problems for public safety. The dissemination and creation of false news through social networks
represents a danger to society, the economic system and democracy [1] because it fuels panic among
people and discredits the scientific community in the eyes of public opinion [7] a point that is reinforced
by our study, since, for most of the articles analyzed it was considered that in times of crisis the amount
of information affects health-related behaviors and emotional responses such as fear, sadness,
nervousness, confusion, anxiety that bring out mistrust reducing the dissemination of useful health
information generating stress and discouragement, affecting the emotional health of the recipients, there
being a positive statistical correlation between social networks and the spread of panic about COVID-
19.
Within the three types of informational context: weak epistemic, strong normative and strong
emotional, in each, but especially the strong emotional context, social networks play a fundamental role
in exploring user behaviors, as they are generally used to manipulate people, being the main media
platforms disseminators of fake news generating many concerns regarding public health and
communication.
According to studies by Alí [1], Córdova [3] and Rocha [7], there is a strong significant correlation
between social network platforms (Facebook, YouTube and Twitter) and fake news. However, in this
study, although the correlation between these platforms and NFs is proven, it should be noted that the
proportions according to the analyzed articles are as follows: the social network Twitter predominated
among the chosen papers appearing in 6 articles, followed by Facebook with participation in 2 articles;
while WhatsApp, YouTube, Instagram, Weibo and Tik-Tok appeared in only one article respectively.
According to the analysis of Pian et al, (2021) [4] the use of social media, the low level of eHealth
literacy and the fast publication process and preprint service are identified as the main causes of the
infodemic. Hypothesis that is reinforced, but complemented in an explanatory way in the analysis of
this study, which highlights that media literacy maintains the objective of being seen as a tool to fight
against fake news and the resilient role of education, as it generates a significant change seeking that
people can make a correct use of information resources validating and through praxis avoid
disinformation [12].
The results of this research include various impacts from small repercussions, such as the spread or
viralization of misinformation to the misuse of drugs to cure the disease. Health misinformation about
vaccines was also very common. But, the susceptibility to interact with FN is independent of the
individual educational level of each study subject as they explained [6]. However, it is stated according
to the results of the
30 articles analyzed that demographic and generational characteristic such as age and the context
where the persons receiving the information analyze it could also influence. For example, the study of
Soleymani (2021) [12] (n=24), explains that each one had a specific attitude towards the crisis,
especially about conspiracy theories.
Currently, artificial intelligence and natural language processing (NLP) and deep learning
techniques are being applied to be able to detect fake news before its propagation via social networks
on covid-19 [3] and [8]. However, for the results of our study not only natural language processing
(NLP) was considered, but in much of the research they use and recommend the improvement of GRU,
LSTM, RNN and PLS-SEM analysis strategies. As well as conducting surveys to collect responses,
give criteria of credibility, conformability, reliability and transferability of information, highlighting
the fine line between the verification of information and maintaining freedom of expression.
7. Conclusion
This analysis has again highlighted the dangers and consequences that fake news presents to
humanity. Infodemic is false or incorrect information in overabundance that makes it difficult for people
to find reliable sources when they need them (WHO, 2020) in such a massive way that it is categorized
as an endemic evil. The causes of misinformation are usually associated with low rates of media and
digital literacy, which in turn makes it difficult for people to distinguish between real or fictitious health
information, being manipulated. Therefore, we conclude by highlighting the need for critical attention
on the part of governments and corresponding authorities in crisis communication and misinformation,
especially for studies focused on public health crises, because as the infodemic of contradictory news
continues to massify, real and timely information cannot be clearly communicated. The three
informational contexts (epistemic, normative and emotional) should be considered, together with media
education to increase trust and emphasize public health messages with emotionally relevant and
scientifically based content on the part of the population. Finally, although the knowledge of NF is well
studied, it is recommended to continue paying attention to the subject matter that harms public health
and safety and to continue conducting research that will allow 100% effective recognition and
elimination of untruthful information in social networks.
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