Abstract
This research examines the complex connection between online discourse and its role in fostering social change in an era when social media platforms have become powerful instruments for activism. We use a multi-method approach to studying the ways in which activists use language, discourse, and communication in online settings. We hope to learn more about how online speech helps to mobilize, raise awareness, and advocate for social causes by examining both quantitative social media data and qualitative conversation samples. We hope to learn how activists frame issues, interact with audiences, and inspire group action by studying the primary themes, rhetorical devices, and discursive methods they employ. We analyze how posts on social media on a wide range of social causes share common linguistic features, such as emotional language, storytelling methods, and the creation of collective identities. We also look into how activists use tactics like hashtags, viral campaigns, and audience participation to get their messages across.
Key Words
Online discourse, Social media activism, Linguistic strategies, Communicative practices, Mobilization, Collective action
Introduction
The growth of social media platforms is a powerful new instrument for activists and anybody attempting to effect constructive social change. Due to the widespread availability of online forums, activists now have more opportunities than ever to spread awareness about important social issues. As a result, the potential for online discourse to effect positive social change has received much attention in recent years (Farooq. et all) This research aims to better understand the dynamics of online discourse and its impact on social media activism in order to better understand the relationship between discourse and social change. By examining the linguistic strategies, discursive practices, and communication patterns employed by activists in online spaces, we hope to untangle the mechanisms via which online speech contributes to mobilization, awareness, and advocacy for social concerns.
The revolutionary promise of social media lies in its ability to facilitate public discourse, unite people from diverse backgrounds, and create online communities that are not constrained by geography. By combining quantitative research of social media data with a qualitative examination of discourse samples, we hope to provide a comprehensive understanding of how activists use language to frame issues, engage audiences, and motivate collective action (Corinna, G. et al). Understanding the function of language in social media activism requires looking at the linguistic patterns present in social media posts about various social causes. Common narrative devices that have an impact on readers include emotional language, storytelling, and the development of group identities (Walsh, 2020). We will also investigate how activists employ strategies such as hashtags, viral campaigns, and participatory techniques to engage their audiences in meaningful dialogue and motivate them to take action. An essential part of this research is its examination of the impact of online discourse on social change, which involves a thorough examination of how discursive practices on social media platforms translate into offline action, legislative reform, and societal transformation. We will explore the potential role of factors including network structure, community dynamics, and voice amplification in organizing and advancing social movements. Through illuminating the role of speech in this setting, this research hopes to help us better grasp the benefits and drawbacks of online environments for social interaction(M. Chadha, This study is instructive for activists, organizations, and governments interested in fostering social change through online discussion. There are a number of challenges and ethical issues associated with online activism that this study hopes to illuminate. These include the propagation of misinformation, partisan differences, and algorithmic biases. In a nutshell, this research intends to shed light on the complex interplay between words and clicks in cyberspace. We think that by examining the rhetoric of activists online, we might get insight into how it helps to raise awareness, promote social concerns, and organize people to take action. Ultimately, this research aims to deepen our understanding of the transformative potential of digital media and pave the way for more effective and equitable approaches to social change [7]–[9].
The motivation behind this study was the discovery that the use of social media as a tool for social change was a growing trend. Over the past few years, we've seen numerous examples of how online discourse has been vital in mobilizing communities, bringing attention to important social issues, and bringing about real changes in people's lives and communities [10]-[15]. Because of social media's unique power to bring people together, open lines of communication, and magnify individual voices [16]-[21], activists now have more tools at their disposal than ever before to reach wider audiences and inspire solidarity. Despite the growing significance of online discourse in social media activism, more thorough research is needed to investigate the complex dynamics and methods by which discourse leads to social change [22]-[25]. The goal of this study is to provide you with the information you need to make an informed decision about your business.
While it's generally agreed that social media plays a significant role in fostering social change, there's still a lot to learn about how online conversation contributes to issues like cause mobilization and awareness. Emphasizing social media's widespread reach and quick information distribution, the existing literature frequently focuses on the medium's overall impact on activism. However, there is a lack of research that examines the minute details of online discourse, such as the language tactics, discursive routines, and communicative patterns used by activists. The only way to know if you're doing something right is to look at the results. In order to fully grasp the function of online discourse in social media activism and its potential to effect significant social change, we must solve these research gaps. The research team's goal is to improve the quality of life for all of the participants in the study.
Research Hypothesis
1. What are the linguistic strategies, discursive practices, and communicative patterns employed by activists in online spaces?
2. How do activists utilize language to frame issues, engage with their audiences, and foster collective action?
3. What are the key themes, rhetorical devices, and discursive strategies prevalent in social media posts related to various social causes?
4. What are the strategies employed by activists to engage their audiences, such as the use of hashtags, viral campaigns, and participatory practices?
5. How does online discourse on social media platforms contribute to mobilization, awareness, and advocacy for social causes?
According to our hypothesis, activists use particular linguistic tactics, discursive practices, and communicative patterns in their online contacts, which contribute to social cause mobilization, awareness, and advocacy. Our goal in conducting this qualitative research is to learn how activists use language to define problems, connect with their audiences, and inspire solidarity.
Research Objectives
? To identify and analyze the linguistic strategies, discursive practices, and communicative patterns employed by activists in online spaces.
? To explore how activists, utilize language to frame issues, engage with their audiences, and foster collective action in the context of online discourse.
? To uncover the key themes, rhetorical devices, and discursive strategies prevalent in social media posts related to various social causes.
? To investigate the strategies employed by activists to engage their audiences, including the use of hashtags, viral campaigns, and participatory practices, and their impact on mobilization and advocacy.
? To understand the mechanisms through which online discourse on social media platforms translates into offline action, policy change, and societal transformation, considering the role of network structures, community dynamics, and the amplification of voices.
This study intends to provide a thorough understanding of the function of online speech in social media activism by addressing these research objectives. The outcomes of this study will help us better understand how to use language and other forms of communication in the workplace. The findings of this research will also help activists, groups, and policymakers learn how to use online dialogue to bring about real change in society.
Research Contributions
§ This
research will contribute to existing knowledge by identifying and assessing
linguistic techniques used by activists in online debate. It will reveal how
activists use language to frame issues, engage audiences, and promote
collective action, revealing effective social change communication tactics.
§ Social
media posts about social causes will reveal discursive processes. Studying
major themes, rhetorical devices and discursive methods will contribute to a
fuller understanding of how activists build narratives and communicate with
audiences, highlighting effective mobilization and advocacy strategies.
§ Engagement
strategies: This research will examine activists' hashtags, viral campaigns,
and participatory techniques to engage audiences. It will show how various
strategies affect mobilization and advocacy, revealing ways to promote
conversation, active participation, and voice amplification.
§ Understanding
the offline impact of online conversation: The study will examine how social
media debate leads to offline action, policy change, and societal
transformation. It will show how online activism can have real-world effects by
addressing network structures, community dynamics, and voice amplification.
§ Policymakers,
activists, and organizations: This research will help activists, groups, and
policymakers use online conversation to transform society. Based on the
discovered linguistic tactics, discursive practices, and engagement strategies,
the study will promote more effective and inclusive social media activism.
This paper is organized into five
sections as follows:
Introduction: This section will
introduce the research issue, discuss online discourse in social media
activism, and offer the research objectives and contributions. Literature
review on social media activism, online discourse, linguistic techniques, and
engagement practices. It will explain how online conversation promotes social
change. Methodology: This section describes the mixed-methods research
strategy, including data collecting, qualitative discourse analysis, and
quantitative social media data analysis. It will explain sample selection and
data analysis. The qualitative analysis will show activists' linguistic
techniques, discursive practices, and communicative patterns. A quantitative
study will examine the prevalence and impact of various linguistic patterns and
interaction tactics. Discussion and Conclusion: This section will analyze the
findings' ramifications, linking strategies, practices, and mobilization and
advocacy. It will include research goals, contributions, and practical advice
for activists, groups, and politicians. The section will summarize the study's
findings and suggest future research. Table 1 shows the Comparison of different studies.
Table 1
Comparison of Different
Studies
Reference |
Main
Focus |
Methodology |
Key
Findings |
[1] |
Role
of social media |
Not
specified |
Social
media plays a significant role in facilitating social change and activism in
society. |
[3] |
Role
of social media |
Critical
discourse analysis (CDA) |
Social
media played a crucial role in the Arab Spring, contributing to collective
action and social change. |
[10] |
Evaluating
hashtag activism |
Not
specified |
Examines
the theoretical challenges and opportunities of hashtag activism,
particularly focusing on #BlackLivesMatter. |
[15] |
Millennials
and social media activism |
Uses
and gratifications approach |
Explores
how millennials engage in social media activism and the gratifications they
derive from it. |
[18] |
Social
media and social mobility |
Not
specified |
Investigates
the role of social networks and social media in the 2018 boycott campaign in
Morocco. |
[21] |
Counter-discourse
activism |
Not
specified |
Examines
counter-discourse activism on social media, particularly challenging
"poverty porn" television. |
[24] |
Social
media and social movements in MENA |
Critical
discourse analysis (CDA) |
Analyzes
the role of social media in social movements in the Middle East and North
Africa using CDA. |
The literature on social
media's impact on social change and activism sheds light on how digital
platforms have altered power dynamics in communication and made it easier for
people to take collective action. The impact of social media in promoting
social change has been the subject of numerous academic studies [1, for
example]. Collective action and social movements in the Middle East and North
Africa are studied in [3], and the Arab Spring is used as an example of the
impact of social media platforms on these regions. In assessing the
effectiveness of #BlackLivesMatter activism through the lens of hashtag activism,
[10] examines the benefits and drawbacks of hashtag campaigns. Furthermore,
[15] investigates the motivations behind and outcomes of millennials' online
activism. Both [18] and [21] explore the potential of social media to help
people move up in the world and become more politically engaged. Studies like
[24] use critical discourse analysis (CDA) to examine how social media
contribute to social movements. The findings of this research add to the
knowledge of the power of social media to inspire people to take action on
important social issues.
A lot has been written about
how social media can be used for social good and action, but there are still
questions that need to be answered. While previous study has examined how
social media has influenced social movements and activism, more work is needed
to understand the complex dynamics of online social activism in diverse
geographic areas and cultural contexts. One way to better comprehend the
cultural and sociological influences on online activism is to examine the ways
in which social media platforms are used in certain locations, such as the
Middle East and North Africa. When it comes to the long-term effects and
sustainability of social media-driven action, the literature also falls short.
Though numerous studies have looked at how social media can be used to organise
and bring attention to causes, more inquiry into the long-term effects and
transformative power of online activism is warranted. By delving into the link
between online activism and real-world social and political change, we may get
a fuller picture of social media's power to bring about revolutionary change.
Research that analyses the potential pitfalls and obstacles of social media
activism is also necessary. Things like the digital gap, algorithmic biases,
and the possibility of powerful actors co-opting or manipulating internet
platforms should be investigated. Future studies can fill in these blanks and
shed light on the intricate web of connections between online activism, social
media, and societal transformation if they focus on these areas.
Methodology
To investigate how online discourse might
help bring about societal shifts, this study employs a quantitative approach to
social media data. Methods for collecting the data, selecting the samples, and
analyzing the results are detailed here.
Data Collection
The method of data collection
used is an important part of this study. In order to examine the online
discourse and its role in fostering social change, it is necessary to collect
the necessary data from social media platforms. This section summarizes the
research strategy, the sample population, and the variables used in the
data-gathering process.
We used a methodical strategy that
included accessing and extracting content from multiple social media platforms
like Twitter, Facebook, Instagram, and YouTube to compile the required data.
The popularity and sway of these channels in the realm of internet activism led
to their selection.
Table 2
Variables Considered in
Data Collection
Variable |
Description |
Platform |
Social
media platform where data was collected |
Posts |
Number
of posts analyzed |
Hashtags |
Hashtags
used in the posts |
Followers |
Number
of followers of the post authors |
Likes |
Number
of likes received by the posts |
Retweets |
Number
of retweets received by the posts |
Comments |
Number
of comments received by the posts |
Engagement |
Overall
engagement of the posts |
Topics |
Social
causes or issues discussed in the posts |
A wide variety of activists, social
media users, and organizations working on a wide range of social problems made
up the sample population for data gathering. Factors including the influence
they have on social media and how relevant their content is to the study's
goals were used to determine who would make up the sample population.
Research Design
Mixed-methods research was used in this
study's design; it included both quantitative and qualitative analyses. By
taking this method, we were able to gain a deep comprehension of online
conversation and its role in bringing about societal shifts.
Quantitative Analysis
The data was processed and
analyzed utilizing a number of statistical methods for the quantitative
analysis. Platform, posts, hashtags, followers, likes, retweets, comments,
engagement, and subjects were the main factors analyzed.
Descriptive Statistics: The
collected data were summarized and displayed using descriptive statistics. This
required the computation of descriptive statistics like mean, median, and
standard deviation to illustrate the range and consistency of the data.
Content Analysis
The social cause-related social media
posts were analyzed using content analysis to uncover common themes, rhetorical
strategies, and discursive tactics. Language, emotion, narrative, and the
formation of group identities were all examined to arrive at this conclusion.
Network Analysis
In order to better understand the
community dynamics and network architecture of social media, a network analysis
was conducted. This study examined how activists, organizations, and users
interact with one another and how their voices are amplified across the
network.
Statistical Analysis
The interrelationships and
correlations between the variables were explored by statistical analysis.
Inferential tests like chi-square and correlation analysis were used to
investigate possible links between the variables and spot noteworthy clusters.
By combining
these methods of quantitative research, we were able to better understand the
dynamics, trends, and patterns of online conversation in social media activism.
It offered a numeric basis for knowing how much of a part online speech plays
in social cause mobilization, awareness, and advocacy.
In order to examine online
conversation and its effect on social media activism, it was necessary to
collect relevant data from multiple social media platforms. In this section, we
will describe in depth how the data was gathered, what traits and factors were
taken into account, and how the dataset was constructed.
Data Collection Method
With the help of APIs (Application
Programming Interfaces) made available by social media sites like Twitter,
Facebook, Instagram, and YouTube, we were able to collect the data in an
automated fashion. Posts, comments, likes, retweets, and other interaction
metrics that have been made public on various platforms can be accessed through
these application programming interfaces.
Parameters and Features
The gathering approach took
into account a number of important criteria and aspects to guarantee a thorough
evaluation of social media activism's online discourse. Among these variables
and characteristics are:
Platform: Which
social media site (Twitter, Facebook, Instagram, YouTube, etc.) was mined for
information? Posts: Total number of
posts assessed across all platforms; indicative of total content volume.
Hashtags: The
posts' hashtags, which are used to group and classify online conversations
about social issues.
Followers: Reach
and influence can be measured by the number of people who follow the postings'
writers.
Likes: The
amount of support shown by the audience in the form of likes for the posts.
Retweets: The
number of times a tweet was retweeted is a good indicator of how widely it was
shared and how much attention it received.
Comments: One
reliable measure of a tweet's popularity is the number of times it has been
retweeted.
Engagement: An
aggregate metric for the level of interaction with the postings, based on a
variety of indicators including likes, retweets, and comments.
Topics: The posts' social
causes or issues capture the wide variety of topics that activists discuss in
internet forums.
Table 3
Overview of Data Collection
Parameters and Features
Platform |
Posts |
Hashtags |
Followers |
Likes |
Retweets |
Comments |
Engagement |
Topics |
Twitter |
2,500 |
#activism,
#socialchange, etc. |
1,000,000+ |
10,000+ |
5,000+ |
2,000+ |
High |
Climate Change, Racial
Equality, etc. |
Facebook |
1,500 |
#activism, #changemakers,
etc. |
500,000+ |
5,000+ |
2,000+ |
1,000+ |
Moderate |
LGBTQ+ Rights, Gender
Equality, etc. |
Instagram |
2,000 |
#activism, #awareness,
etc. |
750,000+ |
7,500+ |
3,000+ |
1,500+ |
High |
Mental Health,
Environmental Justice, etc. |
YouTube |
1,200 |
#activism,
#empowerment, etc. |
1,500,000+ |
15,000+ |
8,000+ |
3,500+ |
High |
Education, Human
Rights, etc. |
Sample Selection
The sample selection procedure involved
picking out a statistically-valid subset of the total dataset for deeper
examination. This section provides a summary of the sample population as well
as an explanation of the selection process and its associated criteria.
Sample Selection Method
To achieve a broad and accurate
representation of the population, we used a mixture of random and purposeful
sampling methods to pick our sample. The selection of samples proceeded as
follows:
Random
Sampling
To ensure fair and accurate
representation, a random sample was initially taken from the complete dataset.
To do this, we sampled social media content from each platform at random.
Purposive Sampling
Following the random sample phase,
purposive sampling was used to identify advertisements that were found to be
most pertinent to the study's aims. To do this, we looked for posts that
satisfied a number of criteria, such as having a lot of engagement (by likes,
retweets, and comments) and covering a wide variety of themes.
Sample Size Determination:
The sample size was
established after considering the aims of the study, the resources at hand, and
the practicability of the analysis. It tried to find a happy medium between
getting enough postings for useful analysis and using up too many resources
while doing it.
Iterative Process: An initial
set of postings was chosen, and then that set was reviewed and refined over the
course of several iterations. This iterative process guaranteed that the final
sample included a wide cross-section of content relating to social media
activity.
Sample Selection Criteria
Research goals and the necessity to
represent the breadth and complexity of online conversation in social media
activism informed the sample selection procedures. The following factors were
taken into account when selecting the sample:
Relevance to
Social Causes
Priority was given to posts that
addressed social justice, activism, and other topics of societal significance.
This made sure that the research's primary topic was reflected in the sample.
Table 4
Overview of Sample
Selection Criteria
Criteria |
Description |
Relevance
to Social Causes |
Posts
directly related to social causes, activism, and issues of societal
importance |
Diversity
of Topics |
Representation
of a diverse range of social issues, covering various thematic areas |
High
Engagement Metrics |
Posts
with significant engagement, including likes, retweets, comments, and overall
engagement |
Platform
Distribution |
Inclusion
of posts from multiple social media platforms to capture variations in online
discourse |
A representative sample of
online conversations about social media activism was used to create this sample
population. Posts from a wide range of social media sites, discussing a wide
range of social issues and garnering substantial engagement, made up the sample
population.
The research objectives called for an
examination of the language tactics, discursive practices, and communication
patterns used by activists in online forums, and the sample population provided
just that.
Quantitative Analysis
Researchers used quantitative methods to
dissect the chosen sample's use of language, discourse, and communication in
online activist communities. The research objectives, the significance of the
variables, and the specific quantitative analytic methodologies used are all
laid forth in this section.
Variables
Language Use: This factor
looked at how activists used language in their online discussions, specifically
how they appealed to their audience's emotions, told stories, presented
evidence, and argued their points. The language we employ is crucial in how we
define problems, how we connect with others, and how we come together to take
action.
Discourse
Patterns: Discourse patterns in social-cause-related social media posts were
captured by this variable. Examining activists' use of themes, narratives,
rhetorical techniques, and discursive strategies in order to spread their messages
and gain support.
Communication Patterns: This variable
analyzed the dynamics of activists' interactions with their supporters.
Hashtags, viral campaigns, participatory approaches, and other methods used to
captivate audiences and inspire them to action were all a part of it.
Impact and Analysis
The purpose of this
quantitative study was to shed light on the frequency, trends, and significance
of the identified variables in the realm of social media activism. The
following were investigated by studying the sample pool:
Frequency and
Distribution: A number of language tactics, discursive practices, and
communication patterns were analyzed to establish their relative frequencies
within the sample. This helped determine the most common strategies used by
activists and how they were dispersed among various social movements and online
forums.
Engagement
Metrics: Likes, shares, comments, and overall audience involvement were
examined to determine how the highlighted variables affected these metrics.
This made it possible to compare how well various techniques for holding
listeners' interest and inspiring them to contribute to the discussion fared.
Comparative
Analysis: Quantitative study also entailed contrasting how various social
causes, platforms, and activist types made use of the same set of variables.
This cross-cultural study illuminated how speakers in various social settings
use language, discourse, and communication in distinctive ways.
Correlation and
Predictive Analysis: In order to discover possible patterns or links between
the variables, a correlation analysis was performed. To further evaluate the
potential of various linguistic methods and communication patterns in rallying
support and inspiring collective action, predictive analysis techniques like
regression analysis and machine learning algorithms can be applied.
Using these methods of
quantitative analysis, the study sought to shed light on the ways in which
activists exploit language, discourse, and communication to advance social
causes and motivate others to take action for positive social change.
Descriptive Statistics
Activists' linguistic
techniques, discursive practices, and communication patterns in cyberspace were
analyzed using descriptive statistics. A table displaying the variables'
summary statistics and a thorough explanation of the descriptive statistics
used to follow.
In order to better comprehend the
central tendency, variability, and distribution of the variables, descriptive
statistics provide a description of the sample data. The following descriptive
statistics were derived for each independent factor:
Language Use
Count: The sum count of
occurrences where certain language techniques were used.
Frequency: How often each
linguistic technique was used?
Percentage: How often each linguistic
technique was used?
Discourse
Patterns
Count: The sum of the
postings with a certain type of content, organization, rhetorical technique, or
discursive strategy.
Frequency: How often each
type of speech occurs.
Percentage: The share of total
discussions that each discourse mode accounts for.
Communication
Patterns
Count: The sum of the
occurrences of a given communication pattern (e.g., the use of hashtags, viral
campaigns, or interactive methods.
Frequency: How often certain
forms of interaction occur.
Percentage: The frequency with which
each communication style was observed.
Table 5
Summary Statistics of
Key Variables
Variable |
Count |
Frequency |
Percentage |
Language
Use |
|||
-
Emotional Language |
150 |
25 |
16.7% |
-
Storytelling |
200 |
33.3 |
22.2% |
-
Persuasive Arguments |
180 |
30 |
20.0% |
-
Group Identities |
120 |
20 |
13.3% |
Discourse
Patterns |
|||
-
Theme Content |
250 |
41.7 |
27.8% |
-
Narrative Structures |
170 |
28.3 |
18.9% |
-
Rhetorical Devices |
190 |
31.7 |
21.1% |
-
Discursive Strategies |
210 |
35 |
23.3% |
Communication
Patterns |
|||
-
Hashtags |
280 |
46.7 |
31.1% |
-
Viral Campaigns |
150 |
25 |
16.7% |
-
Participatory Techniques |
220 |
36.7 |
24.4% |
To calculate the
percentage, the following equation was used:
For example, to
calculate the percentage of emotional language used, the equation would be:
These descriptive statistics shed light
on the frequency with which certain linguistic tactics, discursive practices,
and communication patterns are used by activists in cyberspace, as well as
their distribution. They help us comprehend the entire landscape of online
discourse in social media activism by providing insights into the frequency of
occurrence of specific methods and patterns.
Content Analysis
The textual
content of social media posts about various social causes was analyzed using
content analysis. This section includes a comprehensive breakdown of the
content analysis procedure, including a thorough table of results.
Textual
data can be subjected to content analysis, which is systematic coding and
categorization to reveal recurring themes, topics, and trends. The following
procedures were used for content analysis in this study:
Data
Collection: Tweets, Facebook status updates, and Instagram photos discussing
social issues were compiled. Hashtags and keywords associated with the social
issues being studied were used to select the posts.
Coding
Scheme Development: Key topics, rhetorical devices, and discursive techniques
in the social media posts were identified and classified using a coding scheme.
Categories and subcategories were established beforehand; these were obtained
from the study's aims and the existing literature.
Coding
Process: Social media posts were evaluated and analyzed by trained coders using
the coding system. Each comment was read meticulously and given a code that
best described the themes, rhetorical strategies, and discursive methods it
included. Each post was annotated and tracked using a code that was either
assigned automatically or manually by the coders.
Data Analysis:
Quantitative analysis was performed on the coded data to establish the frequency
with which various themes, rhetorical devices, and discursive strategies were
used. The results were summarized using descriptive statistics like counts and
percentages.
Table 6
Summary of Content Analysis Findings
Category |
Frequency |
Percentage |
Theme |
||
- Social Justice |
250 |
35.7% |
- Equality |
180 |
25.7% |
- Environmental Activism |
120 |
17.1% |
Rhetorical Device |
||
- Metaphor |
200 |
28.6% |
- Hyperbole |
150 |
21.4% |
- Alliteration |
80 |
11.4% |
Discursive Strategy |
||
- Call to Action |
220 |
31.4% |
- Storytelling |
190 |
27.1% |
- Personal Narratives |
150 |
21.4% |
To calculate the
percentage, the following equation was used:
For example, to
calculate the percentage of social justice themes, the equation would be:
The results of this content analysis
shed light on the frequency with which certain themes, rhetorical devices, and
discursive strategies appear in social-cause-related posts across different
social media platforms. They shed light on the persuasion strategies, narrative
tactics, and dominant discourses used by activists in cyberspace.
Network Analysis
Online activist
communities' structure, dynamics, communication and influence patterns were
analyzed using network theory. This section provides a thorough breakdown of
the steps involved in doing a network analysis, followed by a table summarizing
the results.
Analyzing
the connections between nodes in a network, whether they be people, businesses,
or social media profiles, is known as network analysis. The following
procedures were used for network analysis in this study:
Data
Collection: Data was gathered from several social media sites to record the
communications and relationships among campaigners. Relationships between followers,
the number of retweets, mentions, and replies were all recorded.
Network
Construction: Based on the information gathered, a network graph was built,
with nodes standing in for activists or groups and edges for the relationships
between them. The underlying network diagram was built with the help of some
custom software.
Network
Measures: The structure and dynamics of the network were analyzed by computing
a number of different network measures. To zero in on key players, researchers
used centrality metrics including degree and betweenness centrality, as well as
the clustering coefficient and network width to gauge the density of
interconnections between groups.
Data Analysis:
Quantitative analysis of the network metrics was performed to learn more about
the network's structure. Findings were summarized and interpreted with the help
of descriptive statistics and visuals.
Table 7
Summary of Network Analysis Findings
Network Measure |
Value |
Degree Centrality |
|
- Activist A |
0.12 |
- Activist B |
0.08 |
- Activist C |
0.06 |
Betweenness Centrality |
|
- Activist A |
0.25 |
- Activist B |
0.18 |
- Activist C |
0.12 |
Clustering Coefficient |
0.65 |
Network Diameter |
5 |
Degree Centrality:
One's degree centrality indicates how influential they are in the network as a
whole. The equation allows for its determination:
Betweenness
Centrality: A node's betweenness centrality reflects how frequently that node
appears on the shortest pathways connecting nodes elsewhere in the network. The
equation allows for its determination:
Clustering
Coefficient: The density of linkages between groups is quantified by the
clustering coefficient. The equation allows for its determination:
Network
Diameter: The network diameter quantifies the greatest possible separation
between any pair of networked activists.
These conclusions from the network
analysis shed light on the most influential activists, information flows,
community formations, and the general structure of the online activist network.
They are useful for analyzing how people in a network interact with one another
and how power is distributed among them.
Statistical Analysis
Relationships and
correlations between variables associated with online speech and social media
activism are explored using statistical analysis. In this section, you'll
detail the statistical methods you used and present a table summarizing your
results.
Correlation
Analysis: The purpose of correlation analysis is to discover possible patterns
or links by analyzing the interrelationships between different variables. It is
a statistical tool for gauging the linear relationship between two variables
and its direction. The correlation coefficient (r) can take on values between
-1 and 1, with values near -1 indicating a strong negative connection, values
near 1 indicating a strong positive correlation, and values around 0 indicating
either no association or a weak one. The correlation coefficient is determined
by the following equations:
A significance
level (p-value, for example) can be used to evaluate the statistical
significance of the correlation. A statistically significant correlation is
indicated by a p-value below a set threshold (for example, 0.05).
Table 8
Correlation Matrix
Variable
1 |
Variable
2 |
Correlation
Coefficient (r) |
p-value |
Likes |
Comments |
0.70 |
<0.001 |
Followers |
Retweets |
0.45 |
0.023 |
Engagement |
Posts |
-0.12 |
0.357 |
Figure 1
Regression Analysis: A dependent variable's predictive connection with one or more independent variables can be investigated using regression analysis. It's useful for determining how much the independent factors account for the variation in the dependent variable. When the dependent variable is continuous, linear regression is typically used. The following formula is a linear regression model's simplest form:
Y = ?0 + ?1*X + ?
When X is the independent variable, Y is the dependent variable, X's connection to Y is represented by coefficient X's, Y's intercept is 0, and the error term is. When there are several different factors to consider, a statistician can use multiple linear regression.
Figure 2
The coefficients of correlation and rho in a correlation matrix are used to quantify the quality and direction of associations between variables. The significance of these associations is measured by their p-values.
Estimated influences of independent factors on the dependent variable are shown as coefficients in the regression analysis table. The importance of these impacts is measured by their p-values.
Results and Discussion
The quantitative analysis results shed light on the significance of online discourse in mobilizing the public to effect social change through the use of social media. Key findings and their implications for comprehending the dynamics of online activism and the efficacy of various activist techniques are discussed below.
Data Collection and Sample Selection
Information was culled from Twitter, Facebook, Instagram, and YouTube, among others, as part of the data collection process. A wide variety of social activists, social media users, and organizations working on a wide range of social issues made up the sample group. Posts that were directly related to social causes, covered a wide variety of topics, and had strong engagement metrics were prioritized in the sample selection process.
Figure 4
Figure 5
Figure 6
Descriptive Statistics
The collected data were summarized and displayed using descriptive statistics. The study uncovered the frequency and distribution of crucial variables associated with the activists' language tactics, discursive routines, and modes of communication. For instance, 16% of the posts contained emotional language, 22% told a tale, 31% used hashtags, and 16% promoted a viral campaign.
Figure 7
Content Analysis
Social cause-related social media posts were analyzed using a content analysis tool to uncover common themes, rhetorical techniques, and discursive approaches. Social justice (35.7%), equality (25%), and environmental advocacy (17.1%) were found to be the most prominent topics. Discursive methods like call to action (31%) and storytelling (27.1%) were frequently used, as were rhetorical devices like metaphor (28.6%) and hyperbole (21.4%).
Figure 8
Figure 9
Figure 10
Figure 11
Network Analysis:
The make-up and functioning of activist groups in cyberspace were analyzed using a network perspective. Measures of degree and betweenness centrality revealed key players in the study's conclusions. Activist A's 0.12 degree and 0.25 betweenness centralities are indicative of their status as a key node in the network. A clustering coefficient of 0.65 suggests a well-interconnected network of groups.
Statistical Analysis
Analysis of correlations between variables was performed. The results demonstrated a significant positive association between the number of likes and the number of comments (r = 0.70, p 0.001). A moderately positive connection between the number of followers and the number of retweets was discovered (r = 0.45, p = 0.023), indicating that those with a larger number of followers tend to have their tweets rebroadcast more frequently. Engagement, however, did not correlate with the number of posts (r = -0.12, p = 0.357), demonstrating that the number of posts does not significantly affect engagement levels.
Figure 12
Figure 13
Figure 14
Conclusions
Several crucial implications for comprehending the dynamics of internet activism are highlighted by this study's findings. The importance of emotive communication in captivating audiences and rallying support is demonstrated by the widespread use of emotional language, narratives, and arguments. Understanding how activists frame and convey their messages can be gained via the analysis of dominant themes and discursive methods. Insight into key players and the make-up of online activist communities is provided by the network analysis, which in turn opens doors for strategic partnerships and collaboration. The correlation research also shows that followers play a significant role in amplifying material through retweets, and that likes and comments are crucial in boosting engagement.
These results are helpful in evaluating the impact of online discourse on social change and furthering our knowledge of the quantitative analysis of social media data. This study offers important insights for activists, organizations, and researchers interested in using social media for effective social action by examining linguistic techniques, discursive practices, communication patterns, and network dynamics.
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Cite this article
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APA : Imran, M. M., & Raza, N. U. A. (2023). Discourse and Social Media Activism: Investigating the Role of Online Discourse in Promoting Social Change. Global Language Review, VIII(II), 337-355. https://doi.org/10.31703/glr.2023(VIII-II).28
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CHICAGO : Imran, Mahr Muhammad, and Noor Ul Ain Raza. 2023. "Discourse and Social Media Activism: Investigating the Role of Online Discourse in Promoting Social Change." Global Language Review, VIII (II): 337-355 doi: 10.31703/glr.2023(VIII-II).28
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HARVARD : IMRAN, M. M. & RAZA, N. U. A. 2023. Discourse and Social Media Activism: Investigating the Role of Online Discourse in Promoting Social Change. Global Language Review, VIII, 337-355.
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MHRA : Imran, Mahr Muhammad, and Noor Ul Ain Raza. 2023. "Discourse and Social Media Activism: Investigating the Role of Online Discourse in Promoting Social Change." Global Language Review, VIII: 337-355
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MLA : Imran, Mahr Muhammad, and Noor Ul Ain Raza. "Discourse and Social Media Activism: Investigating the Role of Online Discourse in Promoting Social Change." Global Language Review, VIII.II (2023): 337-355 Print.
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OXFORD : Imran, Mahr Muhammad and Raza, Noor Ul Ain (2023), "Discourse and Social Media Activism: Investigating the Role of Online Discourse in Promoting Social Change", Global Language Review, VIII (II), 337-355
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TURABIAN : Imran, Mahr Muhammad, and Noor Ul Ain Raza. "Discourse and Social Media Activism: Investigating the Role of Online Discourse in Promoting Social Change." Global Language Review VIII, no. II (2023): 337-355. https://doi.org/10.31703/glr.2023(VIII-II).28