One of the strengths of the memes is that memers may conunent on any political, social, cultural, and religious issue in a humorous a. satirical manner. Moreover, memes have become very popular among users due to their humorous nature and short duration. R may have very strong effect on their perceptions and opinions about different personalities and issues. So, it is import. to explore the nature and type of contents of memes and their impact on perceptions a. opinions of the users. RESEARCH OBJECTIVES • To explore the types/categories of memes. • To explore the way contents of memes are presented on social media. • To explore the impacts of contents of memes on ethical values of users. • To investigate the influence of memes on opinion of users regarding different issues and personalities. • To find out the use of memes for promotion of brands on social media. RESEARCH QUESTIONS RQ1: What are the types/ categories of memes? RQ2: How contents of manes are presented on Social Media? RQ3: How contents of mem. are having an impact on ethical values of users? RQ4: How memes influence the opinion of users regarding different issues and personalities? RQ5: How memes are used in promotion of bran. on Social Media

1. Data Analysis
The present study was designed to examine the effects of social media memes on social media
users’ perceptions. A qualitative research method was employed to meet the research
objectives. For this, two platforms of social media, Twitter and Instagram were adopted to
collect the most popular memes. Twenty-five memes were gathered from Instagram and
twenty-five memes were gathered from Twitter. A total of fifty memes based on images and
videos were selected for this study. These memes were viral from 1st January to 30th April 2022.
All the memes were selected as their presence on social media and the motif behind them. As
qualitative data analysis requires a systematic process for evaluation as a collection of data,
transcription, coding, software analysis, visualization, and explanation (Cohen et al., 2018).
In this study, the collected information was described under parent themes for the partial and
collective explanation. All the nodes based on specified codes were organized and assessed by
the triggers. The analysis has been done through NVivo 12 Software. The content analysis
approach was employed in this study. The phase coding and sub-coding technique are used
under specific themes to analyze qualitative data. The content analysis approach is useful to
analyse pictorial, graphical, and video-based data in terms of systematic categorization
(Belotto, 2018). In this way, an emphasis has been paid to systematic graphical characteristics
used by social media users. All the codes are assigned to nodes. A repetition of nodded images
was compared through coded matrix query, cluster analysis, word mapping, and comparative
file classification have been performed. The exploration and visualization of data were based
on a cluster by word similarity query, matrix coding query, coded analysis by nodes of sources,
and nodes exploration with associated sources. The interpretation based on qualitative content
analysis has been made without any conflict of interest. The detail of the analysis is presented
in the following pages.
Themes and Subtheme Development
The purpose of theme development was to uncover the nature and type of memes as content
used in social media. The images (memes) were classified as informational/educational,
political, promotional, religious, and social/cultural memes. Using this classification, the
hierarchy of themes was developed. There were seven major themes including the reference
codes based on memes narratives. These themes are as follows:
1. Awareness
2. Factual

2. 3. Humiliating
4. Humorous
5. Roasting
6. Serious
7. Trolling
Figure 1
Coded Matrix Based on Parent Codes of Memes Type
A coding matrix query was applied to the number of references to examine the dimensions of
memes towards nature and types. The memes were assigned under seven major themes. All
those memes were generated according to their nature and content presentation. It can be
noticed that the radar pointed out humour, and trolling more than other themes. The
directions of links are related to those themes with a greater amount in comparison to other
types of themes.

3. Figure
1
Overview
of
Concept
Map
based
on
Coded
Structure

4. Figure 2 explains the gaps and busiest textual traffic can be identified through comparative mapping of
codes. A concept mapping query was used to explore the associated items, files, code directions, and
dimensionality. A massive bunch of concepts was identified between the memes and their types being
developed. The majority of code connections were associated with those memes. Although, the
interrelated links among file classification, linear relationships, themes, and images displayed the
conceptual direction of conversations. But most of the links were found in the social/cultural dimension
with humour and trolling memes types.
Figure 3
Items cluster by word similarities
A cluster analysis query based on the word similarity of nodes was employed to generate patterns of
codes. A word tree of clusters under the classification of various codes (nodes) of themes the analyzed
closely. The machine algorithm precisely axial the simultaneous codes by their group of contexts.
Figure 3 displays the context similarities with relative words and combines them in the cluster. A more
excellent organization is at the top of the cluster with humour, roasting, humiliating, and trolling. As
factual related to serious.

5. Figure 4
Figure
4
Comparative
analysis
of
memes
type
and
memes
nature
used
in
social
media

6. Figure 4 presents a comparative analysis of meme types and memes’ nature as per their presence on
social media. The greater percentage of memes on social media were related to humour, and trolling
was associated with political and social/cultural memes. The columns of matrix coding indicate that a
higher percentage of memeswere serious (65.71) and trolling (50.91%) associatedwith politics, humour
(65.56%), and humiliating (51.56%) with a social/cultural nature.