Research on the Influencing Factors of Consumers' Purchase Intention of Commuter Pants Based on UGC —— Case Study of “Little Red Book” App

: The Little Red Book App is a typical representative of User-Generated Content (UGC) platform in China, being well-known to the public for its unique sharing function. In this app, numerous users sharing content related to commuting clothing. However, there are very few research on the consumption intention of commuter pants consumers on the UGC platform. This study examines how UGC on the Little Red Book APP influences users' consumption willingness, using the 100 top commuter pants notes about popular commuter pants content as experimental subjects from the Little Red Book platform. Text analysis and network research are conducted based on data collected from Little Red Book open API “Dandelion” platform. information quality, visual experience and KOL influence significantly influence consumers' purchase intention. This study summarizes the common denominator of the most popular notes for relevant search terms from multiple perspectives and provides insights into how to utilize UGC and KOLs marketing to stimulate consumption desire and promote product sales. Based on the research results, corresponding feasible suggestions have been proposed for UGC e-commerce platforms, brands, and KOLs.


Research Background and Purpose
With the popularity of social media and the retail model has undergone profound changes under the new situation, User-Generated Content (UGC) has become an important touchpoint where consumers obtain product information and make purchasing decisions.Recommending and selling products through the UGC platform is essentially a social e-commerce model [1].UGC platforms have the characteristics of freedom, simplicity, and decentralization, easily making it for users and users, users and platforms to form interactive connections and causing resonance and trust among other consumers [2].UGC platforms and influencers shape consumers' perceptions and stimulate their desires for products through spreading information, interacting with users and providing visual experiences.As a typical representative of UGC websites, the Little Red Book platform is well-known to the public for its unique sharing function [3].However, factors impacting consumers' purchase intention in the UGC and KOL marketing context need to be further explored.This study selecting 100 top popular commuter pants notes from the Little Red Book platform as research samples.Based on data collected from the Little Red Book platform open API to mine text and analysis content.This study examines UGC on the Little Red Book APP influences consumers' purchase intention, provides insights into how to utilize UGC and KOL to stimulate consumption desire and promote product sales, proposes recommendations for e-commerce platforms and brands.

Research Status
The author conducted a search on the topics of "Little Red Book" and "UGC" in the CNKI database, with a total of 155 related papers, including 100 academic journals and 50 master's papers.After analysis, the author found that the existing research perspectives mainly focus on the following three aspects: 1) Research on factors that affect consumer purchasing intention.For example, based on SOR theory Tan Shunxin found that the influence of social e-commerce UGC characteristics on users' purchase demand is obvious and positive [4].
2) Marketing strategy: in this paper, the author always choose case study.Such as Lu Xizhe clearly analyzes the marketing strategies which success or need to improve in YC, and elaborating the problems of YC brands marketing strategies, the author gave specific suggestions on the optimization of the Little Red Book platform in terms of mechanism, content and organization [5].
3) Social community: for instance, Chen Zhu released a study of the Xiaohongshu youth coffee community [6].

Method
This study is conducted by a combination of qualitative method with quantitative method.

Network Research Method
By searching for keywords such as "commuter pants", "commuter look" and "ootd pants collection" on the Little Red Book platform, the author selects the "hottest" ranking on the Little Red Book platform and obtains the top 100 notes with the highest praise in the search results of relevant search terms in 2022.Through the official Dandelion platform of the Little Red Book platform, the author can obtain the reading volume, likes, total comment volume and other relevant data of each note.

Text Analysis Method and System Functional Language Method
Text analysis will be used to analyze symbols that convey a variety of specific meanings, and combine the methods of semiotics, structuralism and linguistics to continuously discover the deeper message from the content of the text, so as to deeply understand the media reality presented by the media for the audience [7].In this paper, the text content of 100 notes is collected to build a corpus.This paper uses WeiCiYun to summarize the high-frequency words used in the explosive notes conducts a data analysis of it.Through the discourse analysis of the title by systemic functional language method, the author combined with the click through rate to analysis the common types of popular note titles.

Literature Research Method
Through academic platforms such as HowNet, this paper uses literature resources such as master's and doctor's theses, journals, and related e-commerce conference papers to sort out the literature on the Little Red Book platform, consumer purchase intention, KOL and KOL marketing theory, information communication theory and other research materials.The author combined with research content to provide theoretical support for the following research and formulates a research framework.

Word Frequency Statistics of All Text Content
The corpus summarizes the top 100 notes on commuter pants on the Little Red Book platform in 2022, with a total of 12606 words.Through the WeiCiYun software, the word frequency statistics of all text content and generate the word cloud map of keywords from notes are selected.As a more intuitive way of information visualization, word cloud can clearly distinguish the importance of different keywords in the text (see Figure 1).The larger the font, the more frequently the keyword appears in the relevant text.

Keyword Cloud of Title
From the keyword cloud in Figure 2, it can be seen that when the bloggers of the 100 popular notes release relevant notes usually choose keywords that directly point out the main subject of the notes, such as "pants", "suit pants", "commuter", "worker", "pants collection", etc, to be used in the title and also uses words such as "simple", "exquisite", "comfortable", "advanced" to describe the style information of commuter pants; or clearly mention the brand information of pants like "Hermes", "UNIQLO", etc.

Keyword Cloud of Content and Details
The result of Figure 3 show that, in terms of text, bloggers usually introduce the fabric, version like "floor pants, straight pants", fitting effect, brand and style information, matching ideas like "white shirt, T-shirt, cardigan, vest", color, size, price of pants.The words about details of commuter pants have a high frequency, showing that users in the Little Red Book platform focus on the comfort and functionality of the products themselves.This reflects that the content creators pay attention to information quality and visibility in content creation and understand the real needs and interests of users.It is advisable the use of text boxes in this case.

The Choice of Vocabulary
The choice of vocabulary can reflect people's stand and tendency [8].Based on the characteristics of UGC platform, the words selected by bloggers in the text content of their notes can clearly reflect the author's subjective attitude towards the product.The blogger's evaluation of the product affects the consumer's demand for the product, so the vocabulary selection results of the popular notes also reflect the user's main interests for related products.From the Figure 4 the proportion of speech, the adjectives and adverbs used in the most popular notes account for about 20% of the words in the full text.In addition to the objective description, bloggers also have a large number of subjective evaluations in the introduction of products.By further selecting the word frequency of adjectives of the corpus in Figure 5 bar chart for analysis, it can be found that the word frequency of "comfortable", "simple", "loose" and "comfortable" is the highest, followed by "exquisite", "fashionable", "lazy" and "texture".This shows that in 2022, users' demand for commuter pants will mainly focus on comfort and skin feeling, followed by style.

Type of Notes
The form and other data such as content, images, influencer profiles, likes, comments, and clickthrough rates of the top 100 notes collected in Excel table.As Figure 6 show that there are 52 text notes and 48 video notes in total.It means that among the notes related to commuter pants in 2022, the top 100 notes with the highest popularity choose an average release form, and the number of pictures notes is slightly larger than video notes.Among them, the average number of likes of a single video note is 17000, the average number of collections is about 9860, and the average number of comments is about 413; The average number of likes for a single pictures note is 15000, the number of collections is about 9050, and the number of comments is about 300.Overall, the interactivity of video notes are stronger than pictures notes.The introduction of commuter pants in the video notes mainly includes product evaluation, matching display, pants collection recommendation and so on.Combined with sound, picture and color, bloggers who publish videos will display products in a richer way than pictures notes.They use more spoken expressions and try on pants by themselves, which noun verb adjective name brand adverb helps to enhance consumers' sense of real experience, make it easier for them to accept the suggestions of bloggers, and reduce their resistance to brand marketing promotion.While pictures are easier to be modified and beautified.Due to the demand of bloggers to receive brand advertising, the authenticity of pictures notes will be lower than video notes.The way to show products in pictures is relatively simple, which will affect the purchase intention of fans to a certain extent.
Figure 6: Type of notes (Picture credit: Original).

Major Topics of Notes
Text mining found that the popular notes mainly focus on 5 major topics: product recommendation (45%), styling tips (20%), commuting stories (5%), travel tips (8%), shopping sharing (20%) and life essays (2%).Among them, the product recommendation type has the highest reading volume and interaction, indicating that this type of content can stimulate users' purchasing desires most.This also verifies the argument that the product recommendation role of UGC content is welcomed by users.

KOL Characteristics
Through the official dandelion platform of the Little Red Book, the author analyzed the account data of 100 note bloggers and got 51 pieces of relevant data, of which 49 bloggers were not registered on the official platform, so the author could not get the data of corresponding notes.Based on UGC theory, the suggestions of Key Opinion leader have an important impact on the consumption demand of other users [9].By analyzing the relevant data of the selected 51 text of notes and the account data of the bloggers, it can draw relevant conclusions.

Gender of Fans
According to Figure 7, the proportion of female users in the total number of fans of the accounts to which the popular notes belong, about 88% data of accounts which the popular notes belong show that the proportion of the female fans account for 97% or more of the total number.It can be concluded that the most popular commuter wearing bloggers have a common feature that the proportion of female fans is very high.

Age Distribution of Fans
Among the 51 notes, the age portraits of fans in 28 accounts are mainly concentrated in aged 25-34, and the titles of 28 notes do not indicate prices of commuter pants and other related information; The age portraits of fans in 23 accounts are mainly concentrated in aged 18-24, including 8 notes with "parity" in the title or indicate that the price of product less than 100 yuan.This shows that the target users of related commuter products are mainly female customers aged 25 and above, while users under 25 will pay more attention to the price of commuter pants when purchasing related products.

Fan Quantity
As Figure 8 shows that among the 100 accounts of bloggers, there are 11 bloggers have fans less than 1W, 21 bloggers with more than 1W and less than 5W fans, 37 bloggers between 5W and 20W, 17 bloggers with more than 20W and less than 50W followers, and 13 bloggers with more than 50W followers.From the above data, it can be concluded that: 1) There are few KOLs (more than 500000 fans) in the head of commuter fashion, but the influence and natural flow of fans in the head KOL are large; The top bloggers' works are much more popular than those of other levels.For the brand side of the product, the cooperation with the head blogger is easier to quickly improve the brand exposure and sales [10].
2) Waist KOL (50000-500000 fans): such bloggers account for the main proportion of the creators of popular notes.Although the number of fans of a single blogger is lower than that of the head blogger, the release effect of the notes can reach the influence of the head blogger.And this kind of blogger has more replies to fans than the head blogger.The positioning of blogger is more affinity and realistic, and the adhesion of fans is higher.
3) Tail KOL (less than 50000 fans): it is less likely to create popular notes, but the fan interaction data of a single popular note is more authentic.KOL in the tail is more diversified, and the content released covers a wider range.It lacks the verticality of the account, but it is closer to the daily life of ordinary consumers.Such bloggers are generally consumers and spontaneous content creators.For brands, encouraging tail bloggers to spontaneously release notes related to products on the platform can also achieve good communication effect and reduce the publicity cost of brand promotion.

Conclusion
This study conducts empirical tests based on data from Little Red Book APP and verifies that factors such as information quality(vocabulary, product information etc.), visual experience (type of note etc.) and KOL influence significantly influence consumers' purchase intention.Based on the above research result, the study proposes the following suggestions.
1) E-commerce platforms could include UGC content recommendation algorithms in marketing tools, especially strengthening the push of product recommendation content from ordinary users.
2) Brands needs to choose suitable bloggers who have high professionalism for cooperation based on their own needs and use their influence to drive fans' attention to products.
3) Encourage users to create high-quality UGC content and provide content creation guidance to cultivate users' content production motivation.The platform could reward new users who produce attractive content.
4) The platform needs to review the authenticity of the content shared by users, punish and restrict the publication of content that contains false promotion of product efficacy and other illegal information.
However, the applicability of research conclusions needs to be further tested due to the limitations of data sources and research scope in this study.

Figure 3 :
Figure 3: Keyword cloud of content and details (Picture credit: Original).

Figure 5 :
Figure 5: The word frequency of adjectives (Picture credit: Original).

Figure 7 :
Figure 7: The proportion of the female fans (Picture credit: Original).