Information Dissemination and Perception by Social Media Users:
Urban Planning Conflicts
Alexander A. Kharlamov
1,2,3,4 a
, Aleksey N. Raskhodchikov
5b
and Maria Pilgun
6c
1
Institute of Higher Nervous Activity and Neurophysiology, RAS, st. Butlerova, Moscow, Russian Federation
2
HSE University, Pokrovsky Blvd., Russian Federation
3
Moscow Institute of Physics and Technology, Institutskiy per., Dolgoprudny, Moscow Region, Russian Federation
4
Moscow State Linguistic University, st. Ostozhenka, Moscow, Russian Federation
5
Moscow Center of Urban Studies ‘City’, st. Leninskaya Sloboda, Moscow, Russian Federation
6
Russian State Social University, st. W. Pieck, Moscow, Russian Federation
Keywords: Perception, Social Media, Neural Network Approach, User-Generated Content, Actors, Digital Platforms.
Abstract: This paper presents an analysis of Information dissemination and perception by social media users in urban
planning conflicts. The study involved a cross-disciplinary approach. The neural network technology
TextAnalyst 2.3 was used as a tools. The material for the study was data from social networks, microblogs,
blogs, forums, video resources concerning reviews of the
South-East Chord
construction in Moscow.
Analysis of Information dissemination and perception by social media users showed that the growth of
negative perception is more actively formed and disseminated through personal accounts, thus enabling
involvement of a large audience and achieving a higher degree of involvement. Meanwhile, there is a more
effective spread of a certain type of perception in communities.
1 INTRODUCTION
The digital space has become the central
communication sphere; therefore, the study of the
characteristics of the information dissemination and
perception, as well as its impact in the network
environment, is an important and urgent scientific
task. The specificity of the information dissemination
in social networks has already received a multi-
dimensional coverage in scientific research (Wang et
al., 2016; Yang et al., 2019; Ranganathan et al.,
2023).
Methods of analyzing communication activity on
the Internet open up new opportunities for identifying
and researching various social conflicts. This is
especially true for large cities and megacities, since
the urban environment has an increased potential for
conflict (Debord, 2020). A large crowd of people in a
small area, the difference in interests of different
groups generate hundreds of conflicts that are
difficult to track and regulate.
a
https://orcid.org/0000-0003-2942-5101
b
https://orcid.org/0000-0001-6814-9029
c
https://orcid.org/0000-0002-8948-7075
One of the frequent causes of urban conflicts are
projects for the development or reconstruction of
urban infrastructure facilities. Large construction
projects disrupt the habitual way of life of citizens and
create temporary inconveniences. In addition, the
interests of city authorities, big business and city
residents often clash here. A major highway, which is
necessary for a city, can at the same time create
significant inconveniences for residents of the areas
through which it passes (Raskhodchikov, 2017).
One of the important tasks of the city authorities
is the settlement of emerging disagreements, the
correction of situations that threaten public peace.
"To govern is to correct," Confucius said. Since most
conflicts are easier to resolve at the very beginning,
without waiting for escalation, management bodies
should be able to identify them in a timely manner
and correctly assess the threat of an undesirable
development of the situation (Raskhodchikov,
Kharlamov, Pilgun, 2020). The method of analysis
presented in the article on the example of a conflict
situation around the construction of a major highway
Kharlamov, A., Raskhodchikov, A. and Pilgun, M.
Information Dissemination and Perception by Social Media Users: Urban Planning Conflicts.
DOI: 10.5220/0011907000003612
In Proceedings of the 3rd International Symposium on Automation, Information and Computing (ISAIC 2022), pages 125-130
ISBN: 978-989-758-622-4; ISSN: 2975-9463
Copyright
c
2023 by SCITEPRESS – Science and Technology Publications, Lda. Under CC license (CC BY-NC-ND 4.0)
125
(South-eastern chord) in Moscow demonstrates the
ability to predict the risks of urban conflicts.
The objective of this study are analysis of the
characteristics of the information dissemination and
perception by social media users to resolve of urban
planning conflicts.
The study involved a cross-disciplinary approach
using neural network technologies. The neural
network technology TextAnalyst 2.3 was used as a
tools (developed by A. Kharlamov) (Kharlamov &
Pilgun, 2020; Kharlamov et al., 2021).
The material for the study was data from social
networks, microblogs, blogs, forums, video resources
concerning reviews of the
South-East Chord
(SEC)
construction in Moscow.
Table 1: Data characteristic.
N Data
Audience
1st
stage
April 1, 2019 00:00 -
June 30, 2019 23:59
352 267
2nd
sta
g
e
July 1, 2019 00:00 –S
e
p
tember 30, 2019 23:59
17 583 997
3rd
sta
g
e
October 1, 2019 00:00 -
December 31, 2019 23:59
65 588 26
4th
stage
January 1, 2020 00:00 -
February 29, 2020 23:59
99 096 49
5th
stage
March 1, 2020 00:00 –
March 31, 2020 23:59
130 180 782
2 RESULTS AND DISCUSSION
2.1 Digital Platforms Analysis
The user content related to the SEC construction is
characterized by a change in the ratio of its
representation in the Internet space, depending on the
time stages, as well as the actors’ preferences.
At the first stage, the content was posted mainly
on social networks (97%), a small part of it appeared
on blogs (2.7%) and less than 1% on microblogs.
The
percentage was calculated by stages from the total
volume of the user content presented in the Internet
space of the studied period.
At the second stage, most of the content remains
on social networks (71.5%), but information activity
in microblogs (16%) and videos (12%) increases;
blogs account for 0.5%.
At the 3rd stage, there is an increase in the volume
of content presented in videos (13.8%), the activity
on social networks (75.6%) increases; and in
microblogs (10%), there is a decrease in interest
compared to the 2nd stage; blogs account for 0.6%.
At the 4th stage, an increase in information
activity in microblogs (19.4%) is revealed, the
representation of content in social networks (70%)
remains the most popular in terms of information
posting, but it decreases in comparison with all
previous and subsequent stages; the representation of
content in videos (8%) also decreased, but the
placement of information on blogs increases to a
maximum rate (2.6%).
At the 5th stage, the content representation in
social networks (79.2%) increases again, while
microblogs (12.9%) and videos (7.5%) retain their
quantitative ratio in the context of the general data set
of this stage; there is a decrease in users’ activity on
blogs (1%).
The results of the analysis of Internet sites
revealed some features of the network users’
involvement in the SEC construction and the
possibility of maintaining their interest in the project,
depending on the time period for the development of
Internet activity, on the type of information source,
and means of attracting the actors’ attention.
The main attention of the Internet audience during
the information activity of the studied time period
was focused on the content of social networks on the
SEC construction. It was the content of social
networks that generated and supported the network
users’ interest in the construction implementation.
The means by which audience involvement was
achieved changed during the development of the
information wave. At the beginning of the conflict
(stage 1), it was possible to maintain the actors’
involvement mainly within communications in social
networks and in news messages; then in the second
half of the year (stage 2), communications in social
networks and official messages were complemented
with communications in microblogs and on video
resources, which retain its relevance at the next stages
as well. At stage 3, video resources are ahead of
microblogs in terms of audience maximization and
actors’ involvement. Stage 4 and 5 are characterized
by the fact that communications in social networks
and microblogs again become the main means of
attracting the Internet audience, and video resources
move to 3rd place (Fig. 1-5).
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Figure 1: This caption has one line so it is centered.
Figure 2: Audience and involvement (stage 2).
Figure 3: Audience and involvement (stage 3).
Figure 4: Audience and involvement (stage 4
).
Figure 5: Audience and involvement (stage 5).
2.2 Sentiment Analysis of the
User-Generated Content
The emotional and semantic characteristics of the
content are also not homogeneous and change at
various stages of the conflict escalation regarding the
SEC construction.
1st stage
The stage is distinguished by the absence of
aggression and neutral sentiment of the content,
which consists mainly of official messages covering
the project planning and implementation (Fig. 6, 7).
2nd stage
This stage is characterized by growing of the users’
interest in the problem. The content is mainly
represented by comments on social networks and
posts.
The overwhelming number of comments suggests
a fairly high level of interest of Moscow residents in
the project. The conclusion is confirmed by the
research data that Internet audiences actively generate
Information Dissemination and Perception by Social Media Users: Urban Planning Conflicts
127
Figure 6: Aggression (aggression is present, strong
aggression, no aggression) in various types of sources
(stage 1)
Figure 7: Content sentiment in various types of sources
(stage 1).
comments and reposts; this parameter is an indicator
of active manifestation of reaction, and the parameter
of actors’ involvement demonstrates the concentration
of network users on posts that reveal various aspects
of construction.
At this stage, a negative sentiment appears, and
most importantly, the presence of aggression and
strong aggression in social networks and microblogs
is observed, which will continue to grow
demonstrating the growth of protest moods and the
residents’ sharply negative attitude to the project (Fig.
8, 9).
3rd stage
This stage is characterized by a sharp increase in the
users’ negative reactions, a further increase in the
negative perception of the SEC construction. The
negative attitude towards the project is manifested in
strong aggression on social networks, on video
resources and microblogs. An important indicator is
the fact that strong aggression significantly exceeds
the indicators of the aggression presence. The user
involvement
reflecting the direct reaction of actors,
Figure 8: Aggression (aggression is present, strong
aggression, no aggression) in various types of sources
(stage 2).
Figure 9: Content sentiment in various types of sources
(stage 2).
shows high values in social networks in the negative
cluster, significantly ahead of the neutral and positive
ones (Fig. 10, 11).
Figure 10: Aggression (aggression is present, strong
aggression, no aggression) in various types of sources
(stage 3).
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Figure 11:
Content sentiment in various types of
sources (stage 3).
4th stage
The network content shows an increase in negative
attitudes towards the project. The protest against the
construction is manifested in aggression and strong
aggression on social networks. An important
indicator is the prevailing negative reaction of the
audience. The number of negative posts and
comments on social networks significantly exceeds
the neutral sector. The user involvement reflecting the
direct reaction of actors, also shows high values in
social networks in the negative cluster (Fig. 12, 13).
Figure 12: Aggression (aggression is present, strong
aggression, no aggression) in various types of sources
(stage 4).
5th stage
The analysis of the content suggests the persistence of
a sharply negative perception of users towards the
SEC construction. The peak in the growth of actors’
activity falls on March 18-25; the sharp increase in
negative assessments was caused by the start of the
construction works, the protest and the act of violence
of the Moscow authorities against the activists on
March 19. The negative attitude towards the project,
the growing protest against the construction is
manifested in the emergence of strong aggression in
social networks. It is significant that strong aggression
Figure 13: Content sentiment in various types of sources
(stage 4).
significantly exceeds the indicators of the presence of
aggression. The quantitative reduction in digital
footprints should be associated with the onset of the
Covid 19 pandemic in Moscow, which significantly
distracted users from the construction problems (Fig.
14, 15).
Figure 14: Aggression (aggression is present, strong
aggression, no aggression) in various types of sources
(stage 5).
Figure 15: Content sentiment in various types of sources
(stage 5).
Information Dissemination and Perception by Social Media Users: Urban Planning Conflicts
129
3 CONCLUSION
This paper presents an analysis of Information
dissemination and perception by social media users in
urban planning conflicts
Analysis of Information dissemination and
perception by social media users in response to the
SEC construction showed that the growth of negative
perception (negative sentiment, aggression, strong
aggression) is also more actively formed and
disseminated through personal accounts, thus
opponents of construction can enable involvement of
a large audience and achieving a higher degree of
involvement. Meanwhile, there is a more effective
spread of a certain type of perception in communities.
The presented method demonstrated the
possibility of assessing the risks of conflict escalation
by tracking the growth of social stress in user texts.
The use of neural networks allows you to quickly
process a large number of messages, as well as
investigate several conflict situations simultaneously.
What makes it possible to use this technology in
modern conditions, given the rapid growth in the
number of communications on the Internet. The
presented technology can be used as one of the
methods of Predictive analytics in management
decision support systems (DecisionSupportSystems -
DSS).
At the same time, it is worth noting that the
effectiveness of neural network technologies depends
on the volume of similar tasks being solved.
Therefore, all kinds of conflicts (Urban planning,
political, social) require separate configuration and
training of the neural network. The advantage of
using neural networks is their learning ability, when
the quality of analysis increases as such tasks are
solved.
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