The Relationship Between Consumer Emotions and Brand Marketing

on Social Media Platforms

Qizhen He

, Ruoxi Wang

and Zhengyue Wang

3,*

Management College, Shanghai University of Engineering and Technology, Shanghai, 200000, China

Media and Film College, Huanggang normal university, Huanggang, 438000, China

Architecture and urban rural planning College, Qingdao University of Technology, Qingdao, 266000, China

Keywords: Consumer Emotion, Brand Marketing, Social Media Platforms, Sentiment Analysis, Purchase Intention.

Abstract: Social media has profoundly transformed consumers’ information acquisition methods and purchasing

decisions. Emotionally driven content makes consumer sentiment a critical factor in brand marketing. This

study investigates how consumers' emotional expressions on social media influence brand marketing

effectiveness. Focusing on the beauty and skincare industry, the research combines questionnaire surveys and

web-crawled data, employing word frequency analysis and sentiment analysis to quantify the impact of

consumer sentiment on brands. The results reveal that 78.4% of consumers believe emotional expressions on

social media affect brand performance, with negative emotions exerting a stronger negative effect.

Additionally, genuine user reviews are found to be more persuasive than advertisements. The study suggests

that brands should establish a public sentiment monitoring system, adjust marketing strategies accordingly,

and enhance product authenticity and user engagement to boost appeal. The findings provide both theoretical

and practical support for precision marketing in the social media era.

1 INTRODUCTION

While browsing rednote, it was observed that many

influencers tend to chase trends and promote products,

yet quickly remove items and avoid further discussion

when issues arise—whether with the product itself or

its endorsers. For example, Winona, a Chinese

skincare brand known for its sensitive skin-friendly

positioning, faced backlash after numerous consumers

reported adverse reactions such as facial redness,

swelling, itching, stinging, rashes, and even skin

cracking. This led to widespread skepticism about its

"sensitive skin" claims, damaging the brand's

reputation and causing a significant drop in market

value.

A product and its associated elements can

influence consumers' emotions and attitudes toward

purchasing, which in turn inevitably affects brand

marketing outcomes on social media. When users on

platforms like Weibo or rednote praise a particular

skincare product, its sales may surge; conversely,

persistent criticism can harm both brand image and

performance. Against this backdrop, the research

question emerges: How do consumers' publicly

expressed emotions on social media impact brands,

and how can these emotions be analyzed to assess

marketing outcomes? The study aims to establish a

real-time public sentiment monitoring system,

enabling brands to conduct targeted marketing

strategy analysis. By leveraging social media insights,

brands can enhance product appeal, improve user

perception, boost sales, and mitigate potential losses.

2 LITERATURE REVIEW

2.1 Characteristics of Brand

Marketing on Social Media

Platforms

2.1.1 Summaries of Current Studies

In recent years, social media has become a vital

battlefield for brand marketing. Brands across

different industries have adopted distinct strategies on

these platforms. Based on a systematic review of

relevant literature, this paper analyzes the

characteristics of brand marketing on social media

platforms, focusing on research subjects, methods,

He, Q., Wang, R. and Wang, Z.

The Relationship Between Consumer Emotions and Brand Marketing on Social Media Platforms.

DOI: 10.5220/0013995900004916

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 2nd International Conference on Public Relations and Media Communication (PRMC 2025), pages 555-564

ISBN: 978-989-758-778-8

555

data analysis approaches, and their corresponding

findings. The study reveals that social media serves

as a crucial channel for brand communication, and

consumer interaction plays a key role in shaping

brand influence. Moreover, brand marketing

strategies should align with the integrated marketing

communications (IMC) framework to enhance

adaptability. However, current research has

limitations, such as insufficient control over

confounding variables, lack of large-scale data

validation, and absence of cross-industry

comparisons. This review provides theoretical

support for future brand marketing studies and

practical insights for enterprises to formulate

effective strategies in the context of social media.

2.1.2 Current Research Status

Existing studies cover a wide range of industries, such

as music festival branding (Fan Yalin, 2023),

influencer marketing in self-media (Xiao Qian, 2022),

luxury brand transformation strategies (Huang Xinya,

2020), higher education service marketing (Ram

Kumar Dwivedi, 2024), and mobile platform

theatrical film marketing (Sang Hyun Nam et al.,

2021). These works explore practical brand marketing

cases in varied market environments, examining the

role of social media in brand communication,

influence building, and market adaptability.

Different methodologies were applied depending

on the research objectives and industry background.

Fan(2023) used case study methods to examine the

marketing communication strategies of specific music

festival brands; Xiao (2022) integrated literature

reviews, original interviews, and questionnaires, and

used SPSS and AMOS for data analysis in the context

of big data and digital economy; Huang (2020)

constructed a marketing strategy model for luxury

brands based on the IMC theory, exploring how social

media facilitates traditional brand transformation;

Ram(2024) conducted empirical research on the

relationship between brand performance and

relationship quality, building a structural equation

model; Sang(2021) used data from the Korean film

industry to analyze how marketing factors affect the

release of theatrical films on mobile platforms.

Existing studies indicate that consumer emotions

have multidimensional effects on brand loyalty. Shen

(2012) focused on time-honored brands and explored

how nostalgic emotions—such as emotional and

preferential nostalgia—affect brand loyalty through

the mediating role of perceived brand value. It was

found that consumer involvement played a

moderating role. However, family or interpersonal

nostalgia had limited impact due to lack of direct

relevance to products. Similarly, research on virtual

influencers showed that emotional engagement

enhanced brand loyalty, with positive consumer

emotions (e.g., affection, trust) acting as key

mediators. Research on hostile brand loyalty revealed

that excessive fan enthusiasm could provoke negative

attitude polarization among other users, with trait

transfer as an important intermediary mechanism.

Quantitative analysis is the primary methodology

used, including surveys, regression analysis, and

structural equation modeling (SEM). For example,

Shen’s study applied SPSS for factor analysis and

correlation testing. Studies on Virtual influencer used

empirical methods to examine how emotional

attachment to digital personas influences brand

loyalty. The hostile loyalty study combined trait

transfer and attitude polarization theories with

experimental and survey methods. While the methods

are solid, they often rely on cross-sectional data,

making it difficult to track long-term emotional and

loyalty dynamics.

The above studies all highlight the importance of

social media platforms in brand marketing, but they

focus on different aspects—music festival branding

emphasizes core brand competitiveness; influencer

marketing in self-media stresses enhancing brand

influence; luxury brand transformation focuses on

adjusting marketing communication strategies; higher

education services center on the quality of teacher-

student relationships and institutional brand

performance; and theatrical films pay more attention

to brand extension. Based on this, it can be inferred

that brand marketing involves multiple dimensions,

and the optimization of marketing strategies can be

approached from various angles.

2.1.3 Literature Review Summary

Research led by Shen established an 'Emotion–

Perceived Value–Loyalty' framework, dividing

nostalgia into product-related and interpersonal-

related types and confirming their differential effects.

This offers valuable insights into emotional

marketing for traditional brands. Virtual influencer

studies proposed a 'digital emotional transmission'

model, showing how virtual personas influence

consumer attitudes in digital contexts. Hostile loyalty

research introduced attitude polarization theory from

social psychology, uncovering emotional contagion

within brand communities and offering warnings for

brand crisis management.

Three methodological features stand out: 1)

refinement of measurement tools (e.g., localized

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nostalgia scales); 2) diversity of analytical methods

(e.g., SEM, multilevel modeling); 3) expansion of

research settings—from offline to online

environments. However, there are clear limitations:

reliance on self-reports, lack of longitudinal tracking,

and limited use of neuroscience methods. Ongoing

debates include how to classify emotions (valence vs.

arousal), whether cognitive appraisal precedes

emotional response, and cultural differences in

emotional expression.

While the fundamental framework for studying

emotional impact on loyalty is established, future

research should enhance mechanism precision, adopt

dynamic methods, and integrate interdisciplinary

theories. Especially in the digital age, the traditional

emotion–loyalty model may be evolving and deserves

further academic attention. In summary, consumer

emotion and brand loyalty research has formed a solid

theoretical system and confirmed the importance of

emotion in brand marketing. However, there is room

for improvement in theoretical depth and

methodological diversity. Future research should

integrate interdisciplinary perspectives and adopt

dynamic, multi-method approaches to reveal the

underlying mechanisms more comprehensively.

2.2 The Relationship Between

Consumer Emotion and Purchase

Intention

2.2.1 Summaries of Current Studies

The interaction between consumer emotions and

brand loyalty is a key topic in brand marketing

research. Existing studies explore the internal

mechanisms between these two factors from different

dimensions, but there are limitations in theoretical

frameworks and methodologies. This paper compares

and analyzes the impact paths and mechanisms of

consumer emotions on brand loyalty based on three

representative studies. The research finds that high-

quality products combined with positive emotional

extension significantly improve consumer attitudes

and brand loyalty. Conversely, negative emotions or

excessively fanatic hostile brand loyalty can trigger

negative attitude polarization among other users. In

terms of research methods, current studies often use

quantitative analysis (e.g., SPSS statistics, regression

analysis) and theoretical model construction (e.g.,

trait transfer, attitude polarization theory). However,

they suffer from a single theoretical perspective and

limited empirical samples. Future research should

integrate interdisciplinary theories and adopt mixed

research methods to further explore the dynamic

relationship between consumer emotions and brand

loyalty, providing more comprehensive theoretical

support for brand marketing practices.

2.2.2 Current Research Status

Existing studies show that consumer emotions have a

multidimensional effect on brand loyalty. Shen (2012)

ocused on time-honored brands and explored how

nostalgic emotions (e.g., emotional nostalgia,

preference nostalgia) influence brand loyalty through

the mediating role of time-honored brand perceived

value. It was found that consumer involvement plays

a moderating role. However, family nostalgia and

interpersonal nostalgia had a weaker impact on brand

loyalty due to their lack of direct connection with

time-honored products. Similarly, the study on virtual

influencers found that virtual influencer endorsements

could enhance brand loyalty by increasing consumers’

“emotional engagement,” with positive emotions (e.g.,

affection, trust) serving as key mediators . Moreover,

research on “hostile brand loyalty” revealed the

negative impact of consumer emotions . In the study

Luo ’s study, it was found that fanatic fan emotions

could lead other consumers (e.g., utilitarian users) to

develop negative emotions towards the brand,

resulting in “attitude polarization” and “trait transfer”

as a crucial mediator in this process. Changju tested

the moderate mediation hypothesis using PROCESS

macro and found that consumer resistance indirectly

influenced brand strength by reducing national affinity.

Current research mainly employs quantitative

analysis methods, such as surveys, regression analysis,

and structural equation modeling (SEM). For example,

Li ’s study used SPSS for factor analysis, correlation

analysis, and regression analysis, confirming a

positive relationship between nostalgic emotions and

brand loyalty. Shen’s study empirically explored how

virtual influencer endorsements affect consumer

brand attitudes. The “Hostile Brand Loyalty Study”

combined “trait transfer theory” and “attitude

polarization theory,” using experimental or survey

methods to analyze the negative effects of fan

behavior on brand image. Although these studies are

methodologically mature, they typically rely on cross-

sectional data, which makes it difficult to dynamically

track the long-term evolution of consumer emotions

and brand loyalty.

The analysis results of each study also show

distinct characteristics. In “The Influence of

Consumer Nostalgia on Time-Honored Brand

Loyalty,” empirical findings show that personal

nostalgia, family nostalgia, product nostalgia, craft

nostalgia, and advertising nostalgia are all positively

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557

correlated with time-honored brand perceived value

and brand loyalty; interpersonal nostalgia is only

positively correlated with perceived value. “Virtual

Influencer Endorsement, Consumer Engagement, and

Brand Loyalty” finds that virtual influencer

endorsement positively affects attitude loyalty and

behavioral loyalty. The stronger the consumer’s

emotional engagement and positive feelings towards

the virtual influencer, the higher their brand loyalty.

Thus, virtual influencers play a mediating role in

higher the brand loyalty. In “Fan Behavior, Brand

Commitment? The Influence of Different Types of

Hostile Brand Loyalty on Consumer Brand Attitude

Polarization,” fanatical fan emotions cause other

potential users and utilitarian consumers to develop

negative emotions towards the brand, resulting in

overall negative attitude polarization. Fanatic fan

emotions act as a mediator through trait transfer in this

negative influence on the brand. These studies

emphasize the influence of consumer emotions on

brand marketing but vary in their research focus and

methodologies. The three papers above discuss the

impact of real vs. virtual emotions, nostalgic

emotional value, and negative emotions on consumers.

2.2.3 Literature Review Summary

The research led by Shen(2012) established the

“Emotion-Perceived Value-Loyalty” framework,

innovatively subdividing nostalgia into product-

related (e.g., craft nostalgia) and interpersonal-related

types, and confirming the differential influence

mechanisms of different types of nostalgic emotions .

This research provides important theoretical support

for emotional marketing of traditional brands. In the

virtual influencer-related studies, the “digital

emotional transmission” model was proposed, which

breaks through traditional spokesperson theory and

reveals how virtual personas influence consumer

attitudes through emotional engagement mechanisms.

These findings provide new insights into brand

communication strategies in the metaverse era . The

“Hostile Loyalty Research” introduces attitude

polarization theory from social psychology,

uncovering emotional contagion in brand

communities and offering early warning perspectives

for brand crisis management .

From a methodological perspective, three notable

features emerge: first, the refinement of measurement

tools, such as the localization of nostalgia emotion

scales; second, the diversification of analysis methods,

with advanced statistical techniques such as SEM and

multilevel analysis being widely applied; third, the

expansion of research settings, transitioning from

offline physical environments to online virtual

contexts.

However, existing methods have significant

limitations: first, data collection heavily relies on self-

reporting methods, which are prone to social

desirability bias; second, 90% of studies use cross-

sectional designs, which fail to capture the dynamic

interaction between emotions and loyalty; third, the

use of emerging methods like neuroscience remains in

its infancy. Additionally, three main issues remain

unresolved: first, there is no unified standard for

classifying emotions, with some scholars suggesting a

classification based on valence (positive/negative)

while others recommend a distinction based on

arousal level; second, debates persist regarding the

mediation mechanisms, especially whether cognitive

appraisal precedes emotional response; third, cultural

differences in emotional expression—whether Eastern

collectivism and Western individualism result in

variations in the mechanisms.

Existing research has established a basic

theoretical framework for understanding how

consumer emotions affect brand loyalty, but there is

room for improvement in the precision of the

mechanisms, the appropriateness of methods, and the

integration of theories. Future research should adopt a

more dynamic, multidimensional perspective and

incorporate emerging technologies to advance the

field. In particular, it is crucial to recognize that the

traditional emotion-loyalty relationship may be

undergoing fundamental changes in the digital

consumer environment, warranting sustained

academic attention.

In summary, research on consumer emotions and

brand loyalty has formed a relatively rich theoretical

system, confirming the key role of emotional factors

in brand marketing. However, there is still room for

improvement in the theoretical depth and

methodological diversity of existing studies. Future

research should further integrate interdisciplinary

perspectives and adopt more dynamic, multi-method

approaches to comprehensively reveal the underlying

mechanisms by which consumer emotions influence

brand loyalty.

2.3 The Relationship Between

Consumer Emotion and Purchase

Intention

2.3.1 Current Research Status

Most research focuses on consumer emotions

(positive/negative affect) and purchase intention

(immediate decisions vs. long-term loyalty).

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Confounding variables include demographics,

external environment, and product attributes.

Common methods include surveys using Likert

scales for collecting data and SEM to test emotion–

purchase intention paths, as well as experiments

simulating social media comment scenarios.

Qualitative supplements include in-depth interviews

exploring emotion triggers and content analysis using

sentiment dictionaries to quantify emotions in UGC

texts.

2.3.2 LIterature Review Summary

Research distinguishes between first-time and repeat

purchases. One study on perceived brand value and

repeat purchase intention found that perceived quality,

brand image, and service significantly influenced

repurchase behavior. Positive brand perceptions

triggered emotional responses that strengthened

loyalty. The study suggests companies should work

with trustworthy influencers and boost brand value to

foster positive emotions and encourage repurchase.

Methods included sentiment-based emotion

indexing and classification into positive vs. negative

emotion dimensions. Semantic analysis was used to

extract emotional keywords and build evaluation

systems.

2.3.3 Conclusion

Emotions directly affect purchase intention: positive

emotion increases intention (β=0.51, p<0.001), while

negative emotion decreases it (β=-0.63, p<0.001).

Negative effects are 1.2 times stronger than positive

ones, aligning with 'loss aversion' theory. Brand trust

fully mediates the emotion–intention relationship (68%

mediation effect). Strong brand reputation moderates

the impact of negative emotions (β=0.18, p<0.05).

Vulnerable consumers (e.g., utilitarians) are more

affected by negative brand sentiment. While loss

aversion theory explains this, some argue that short-

term emotion fluctuations have limited impact,

requiring long-term emotional accumulation for

significant changes. Limitations include artificial

experimental settings, cross-sectional data, lack of

neuroscience evidence, and insufficient distinction

between rational and irrational emotions.

3 METHODS

3.1 Study Design

This study employs structured questionnaires and

web crawling techniques to collect data on user

behavior and content. The independent variable is

defined as consumers’ emotional expressions and

attitudes toward the product, while the dependent

variable is the effectiveness of brand marketing.

Control variables include demographic factors such

as age, gender, and region. The primary aim of this

research is to explore the factors influencing

consumers’ attitudes and emotions during the

purchasing process, particularly in relation to

products and their derivatives. Furthermore, the study

investigates how consumers’ publicly expressed

emotions and attitudes on social media platforms, in

turn, impact brand marketing effectiveness. By

constructing a real-time public opinion monitoring

system and conducting effective data collection and

analysis, the authors provide targeted insights into

brand marketing strategies. This approach assists

brands in leveraging social media to enhance product

appeal and user reputation, ultimately aiming to boost

sales and minimize losses.

3.2 Research Object

3.2.1 Research Samples

Target Population: The target population comprises

consumers who pay attention to brand marketing on

social media, with a particular focus on users in the

beauty and skincare sector. The majority of

participants fall within the 18–24 age group,

accounting for 63.9% of the sample—of which 27.8%

are aged 18–21 and 36.1% are aged 22–24. In terms

of gender distribution, 58.8% of respondents are

female and 41.2% are male, indicating a relatively

balanced gender ratio.

Selection Criteria: high-frequency social media

users (meeting the threshold of an average usage of

more than two hours per day); individuals with

experience in brand consumption or active interest in

the beauty and skincare sector; coverage across

diverse regions, age groups, and interest categories to

ensure data diversity.

3.2.2 Sample Size

A total of 97 questionnaire responses were collected.

In addition, approximately 500 posts related to Estée

Lauder on the rednote platform were gathered for

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559

social media data analysis, from which 30 high-

frequency keywords were extracted. The

questionnaire sample size meets the basic

requirements for statistical analysis, such as

frequency and percentage analysis. Data were

collected through both online and offline channels to

enhance diversity and representativeness of the

sample.

3.2.3 Data Collection Method

Questionnaire Survey: A mixed-mode approach was

adopted, combining online distribution with offline

street-intercept surveys. All responses were collected

anonymously to ensure participant privacy and data

integrity.

Social Media Data: Publicly available data were

collected from Rednote, focusing on case content

related to the Estée Lauder brand. The dataset

includes image-text posts, user comments, likes, and

other forms of engagement.

3.3 Research Tools

The questionnaire in this study is structured around

four main sections: “User Behavior on Social Media,”

“Brand Sentiment and Consumer Behavior,”

“Perceived Influence of Social Media,” and

“Effectiveness of Social Media Marketing.” It

comprises a total of 15 questions, with a core focus

on consumers’ emotional expression on social media

platforms. The questionnaire takes a comprehensive

approach by examining respondents’ demographic

information, usage patterns of social media platforms,

attitudes toward brand marketing and public relations,

as well as subsequent emotional responses and

purchasing outcomes. This design ensures both the

completeness and validity of the content.

A variety of question types are included. Single-

choice questions are used to obtain definitive

information from respondents based on pre-set

options, such as “What is your age group?”—

allowing for efficient collection of basic demographic

data. Multiple-choice questions, some of which are

open-ended, allow respondents to select several

applicable options. For example, “What types of

brand marketing content attract you the most?

(Multiple answers allowed): interactive campaigns,

influencer or celebrity endorsements, brand

storytelling and value promotion, authentic user

reviews and evaluations, others.” These questions

help capture the diversity and complexity of

consumer preferences.

Closed-ended questions provide respondents with

clearly defined options, making them easier to answer

and more efficient for statistical analysis. They

facilitate the collection of standardized data, ensuring

consistency and comparability, and are useful for

quickly capturing respondents’ situations within a

predefined framework. In contrast, open-ended

questions allow respondents greater freedom of

expression, enabling the collection of unexpected

perspectives and unique insights. These questions

offer a more comprehensive and in-depth view of the

research topic, particularly valuable in exploratory

studies and in uncovering underlying motivations. In

this questionnaire, both types of questions are

employed in combination: closed-ended questions are

used to gather basic demographic information and

quantify attitudes, while open-ended questions are

designed to obtain detailed explanations and

supplementary information. This mixed approach

enhances both the depth and breadth of the research.

3.4 Data Collection Process

Collection time and place: From January 31, 2025 to

February 24, 2025, questionnaires and network data

were collected in Binzhou, Wuhan and Shanghai.

Investigation implementation process:

Questionnaire Administration: The survey was

disseminated online via a questionnaire platform and

offline through random street intercepts. After

excluding invalid responses, a total of 97 valid

questionnaires were collected. Logical validation of

responses was conducted to ensure data reliability.

Social Media Data Collection: Web scraping

techniques were used to extract data from the rednote

platform. The data were subjected to descriptive

statistical analysis (frequency/percentage), word

frequency analysis using the TF-IDF algorithm, and

sentiment analysis utilizing natural language

processing (NLP) techniques.

Ethical considerations: The questionnaire clearly

communicated the purpose of the study, and all

participants took part voluntarily. All questionnaire

data were processed anonymously, with no personally

identifiable information collected. Social media data

were sourced from publicly available content in

compliance with the platform’s terms of use. Raw

data were securely stored using encryption, and de-

identification was applied throughout the analysis

process to ensure privacy. The study adhered to

ethical standards for social science research and did

not involve the collection of sensitive information.

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3.5 Data Analysis Methods

3.5.1 Data Organization

Preliminary data collection and collation were

conducted using the online survey platform

Wenjuanxing. Subsequently, further manual

screening was performed using Excel to ensure data

quality. Only valid responses were retained for the

final analysis.

3.5.2 Statistical Analysis Methods

Descriptive Statistical Analysis: This study employs

descriptive statistics to analyze the overall

characteristics of the sample, including respondents’

gender, age, social media platforms used, emotional

expression styles, and the influence of brand

marketing. A total of 97 questionnaires were

collected. Among the respondents, 58.8% were

female and 41.2% were male, indicating a relatively

balanced gender distribution. The majority of

participants were aged between 18 and 24, accounting

for 63.9% of the sample. Specifically, 27.8% were

aged 18–21, and 36.1% were aged 22–24, reflecting

a higher level of emotional expression on rednote

among younger users, as well as greater attention to

brand marketing. In terms of social media usage,

74.2% of respondents reported using social media for

more than two hours per day, suggesting that young

people are frequently exposed to the internet and

digital marketing activities (see Table 1).

Table 1. Basic personal information of respondents

project option frequency percentage

female 57 58.8%

Gender male 40 41.2%

under 18 10 10.3%

18-21 27 27.8%

Age 22-24 35 36.1%

25-34 15 15.5%

35 and above 10 10.3%

less than 30 minutes 0 0

Average daily usage 30 minutes -1 hour 7 7.2%

of social media 1-2 hour 18 18.6%

2 hours and above 72 74.2%

Wechat 42 43.3%

micro-blog 18 18.6%

Social media rednote 55 55.7%

platform Tiktok 55 55.7%

other 10 10.3%

Furthermore, with respect to emotional expression

and the influence of brand marketing, the majority of

respondents preferred to share their opinions

privately with friends (74.75%) or chose to either stop

or add a product to their cart based on their

evaluations (86.1%). Additionally, a significant

proportion of participants (78.4%) reported being

easily influenced by brand marketing strategies (see

Table 2).

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561

Table 2. Respondents expressed emotion and brand marketing impact to come

variable option

roportion

Like 82.5%

Commen

30.1%

s to express views on Transmi

69.1%

the brand on social media Publish ori

inal conten

8.2%

Message the brand’s official

accoun

2.1%

Othe

3.1%

Public positive/ne

ative comments 11.4%

Recommendation/Private discussion 74.8%

Actions in response to po- Increase/ Stop bu

86.1%

-sitive/ne

ative emotions Participate in activities 15.0%

Othe

1.1%

Great impac

78.4%

The impact of brand mar

- General impac

10.3%

-etin

on consumption Little impac

11.3%

ot at all 0

Word frequency analysis: Based on user-

generated image-and-text posts related to Est é e

Lauder on rednote, a word frequency analysis was

conducted, resulting in the extraction of seven high-

frequency keywords (see Figure 1, Table 3).

Alt Text for the figure: Word cloud with beauty and gift-related terms: "Advanced Night Repair Eye

Synchronized Complex," "Three-piece set," "Collagen cream," "Liquid foundation," "Boyfriend," "Full line

products," "New Year gift."

Figure 1. High frequency vocabulary of Est é e Lauder images and text posted by users on rednote.

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Table 3. High frequency words extracted by word frequency analysis

wor

word frequenc

Advanced Night Repair Eye Synchronized

Complex

Liquid foundation 7

Three-

iece se

Full line products 5

Collagen cream 5

frien

ew Year

Emotional analysis: Sentiment analysis tools

were employed to analyze user reviews related to

Estée Lauder on rednote, and a corresponding

sentiment analysis chart was generated (see Figure 2).

Alt Text for the figure: Donut chart displaying sentiment percentages: Positive (54.70%), Neutral (25.64%),

Negative (19.66%).

Figure 2. Emotional analysis of users posting reviews of Est é e Lauder on rednote

Among the reviews, 54.7% were positive, 25.64%

were neutral, and 19.66% were negative. Overall,

user evaluations of Estée Lauder on rednote are

predominantly positive. However, a notable

proportion of users expressed neutral or negative

opinions. This suggests that the brand should pay

closer attention to negative feedback in order to better

understand specific areas of dissatisfaction and

improve its products accordingly.

4 SUMMARY OF RESEARCH

FINDINGS

4.1 The Impact of Consumers'

Emotional Expressions on Social

Media Significantly on Brand

Marketing

78.4% of respondents believe that consumer

sentiment on social media influences brand market

performance. 87.6% stated that brand evaluations on

social media affect their purchasing decisions. While

39.2% of consumers develop a more favorable

impression when brands respond to comments, 50.5%

view such responses merely as Public Relations

tactics. This indicates that most consumers prioritize

peer reviews over brand-generated content.

4.2 The Importance of Interactivity

and Authenticity in Successful

Brand Marketing

Survey results show that 72.2% of consumers focus

on "real user reviews and testimonials," while 67%

are drawn to "interactive campaigns." Additionally,

73.2% reported "occasionally or frequently

engaging" with brands' social media marketing

content, suggesting that brands already have an

engaged audience but need more compelling content

to sustain interest. Sentiment and word frequency

analysis of Estée Lauder on Rednote revealed high-

frequency terms such as "scam," "authenticity

verification," "production date," and "shocking,"

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highlighting consumer concerns about product

quality, user experience, and reputation rather than

mere advertising claims.

Secondary Findings: High-frequency search

terms like "Advanced Night Repair," "foundation,"

"Lancôme Absolue," and "Genifique" suggest brands

should allocate more resources to ingredient research,

product innovation, and diversified marketing

strategies for these products to maximize sales and

enhance brand reputation. About brands must

prioritize genuine consumer engagement, transparent

communication, and data-driven product

optimization to thrive in social media-driven markets.

5 CONCLUSION

This study emphasizes how important social media

interactions and customer emotions are to brand

marketing. Brand assessments have a significant

impact on purchasing decisions, and consumer

sentiment on social media is a major driver of brand

performance. For brand marketing to be successful,

interaction and authenticity are essential. Customers

are driven to interactive campaigns and appreciate

real user feedback, which means that in order to gain

their audience's trust and loyalty, marketers need to

interact with them in a meaningful way. Consumer

worries over product quality and brand reputation are

revealed by sentiment analysis and word frequency

studies, underscoring the necessity for firms to put

transparency first and take proactive measures to

resolve these problems. In conclusion, in order to

improve their market performance and cultivate

enduring loyalty in the digital age, brands should

prioritize genuine consumer involvement and open

communication.

AUTHORS CONTRIBUTION

All the authors contributed equally and their names

were listed in alphabetical order.

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