• Information Systems Review
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• v.20 no.3
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• pp.73-92
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• 2018

Many users are uploading their daily life activities on SNS and use hashtags to describe their postings. Hashtag has the advantage of letting users specify categories for their postings, however until now, the users has had to manually input the hashtags which has been very inconvenient for them. Therefore, in order to address this issue, this paper proposes a hashtag recommender system which recommends proper hashtags to users based on their uploaded images on SNS. The proposed system is designed using four analytic structures, which is composed of a camera information-based analysis, an address-based analysis, a location based CF analysis, and an image-based analysis. In order to check whether the proposed system is improved compared to the existing systems in terms of the hashtag recommendation function, we conducted an evaluation with 212 SNS users from fifteen countries. As a result of the evaluation process, the proposed system shows very high accuracy recommendation results compared to the existing hashtag recommender systems.

• Journal of the Korean Society of Clothing and Textiles
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• v.43 no.1
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• pp.1-16
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• 2019

This study explores the effect of hashtag type on consumer response via evaluations of SNS fashion influencer and information in the context of fashion product communication. The moderating effect of perceived fit between hashtag content and fashion product image on information evaluation was also investigated. An online survey was conducted, and responses from 152 Instagram users were collected. The results indicated that hashtag type (informative vs storytelling) affects the evaluations of influencer and information. First, the informative hashtag has a positive effect on influencer's expertise and usefulness of information. Meanwhile, storytelling type has a positive effect on the familiarity of the influencer. This study also verified the mediated paths from hashtag type to consumer response through the evaluations of SNS fashion influencer and information. The influencer's expertise and familiarity mediated the effect of hashtag type on consumer response. In the information evaluation, only the mediating effect of usefulness was significant. Finally, the high condition of the perceived fit between hashtag content and fashion product image was found to highly evaluate the trust of information. This study extends the scope of fashion communication research from various angles by examining the role of the hashtag as a new type of information source.

• Fashion & Textile Research Journal
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• v.17 no.6
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• pp.942-955
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• 2015

Hashtag has emerged and become one of cultural trend. Given that more and more firms in the fashion industry are using hashtag on images based on SNS to provide information of their products and to communicate with their customers. Especially, hashtags through voluntary participation of users provides the perspective of how customers consume their products. Therefore, this study focused on the using motives of hashtag in image based SNS with customer social participation as mediator towards brand equity. The purpose of this study is (1) to investigate the usage motivation of hashtag of image contents based SNS, (2) to expose how each usage motive affects customer social participation and (3) to find out how customer social participation has an effect on brand equity. In order to achieve the objectives of this study, first we conducted an in-depth interview on 8 image based SNS heavy users to understand the using motives of hashtags. Furthermore, we conducted online surveys amongst people aged between 20s and 30s of image contents based SNS users. As a result of this study, followings were figured out. First, four of usage motivation of hashtag were examined through in-depth interview and previous studies; interest sharing, social interaction, ease of use and enjoyment. Second, usage motivation of hashtag has a significant effect on customer social participation. Third, customer-media participation and customer-customer participation impact positively on brand equity. Lastly, level of customer social participation has the moderating effect on the relationship between motivation of hashtag and customer social participation.

• Journal of Information Science Theory and Practice
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• v.6 no.2
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• pp.46-61
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• 2018

The mobile social networking application Instagram is a well-known platform for sharing photos and videos. Since it is folksonomy-oriented, it provides the possibility for image indexing and knowledge representation through the assignment of hashtags to posted content. The purpose of this study is to analyze how Instagram users tag their pictures regarding different kinds of picture and hashtag categories. For such a content analysis, a distinction is made between Food, Pets, Selfies, Friends, Activity, Art, Fashion, Quotes (captioned photos), Landscape, and Architecture image categories as well as Content-relatedness (ofness, aboutness, and iconology), Emotiveness, Isness, Performativeness, Fakeness, "Insta"-Tags, and Sentences as hashtag categories. Altogether, 14,649 hashtags of 1,000 Instagram images were intellectually analyzed (100 pictures for each image category). Research questions are stated as follows: RQ1: Are there any differences in relative frequencies of hashtags in the picture categories? On average the number of hashtags per picture is 15. Lowest average values received the categories Selfie (average 10.9 tags per picture) and Friends (average 11.7 tags per picture); for highest, the categories Pet (average 18.6 tags), Fashion (average 17.6 tags), and Landscape (average 16.8 tags). RQ2: Given a picture category, what is the distribution of hashtag categories; and given a hashtag category, what is the distribution of picture categories? 60.20% of all hashtags were classified into the category Content-relatedness. Categories Emotiveness (about 4.38%) and Sentences (0.99%) were less often frequent. RQ3: Is there any association between image categories and hashtag categories? A statistically significant association between hashtag categories and image categories on Instagram exists, as a chi-square test of independence shows. This study enables a first broad overview on the tagging behavior of Instagram users and is not limited to a specific hashtag or picture motive, like previous studies.

• Informatization Policy
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• v.29 no.3
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• pp.82-104
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• 2022

One of the interesting social phenomena in short-form video platforms is the hashtag challenge wherein ordinary users are encouraged to create by imitating short viral videos on a particular theme. Despite the increasing popularity of hashtag challenges, theoretical discussion on related user behavior is still very insufficient. In this study, we attempted to examine the impact of micro-influencers in order to understand users' willingness to participate in hashtag challenges. For this purpose, the para-social interaction theory and imitation behavior literature were adopted as key theoretical basis. In an empirical investigation using 243 survey data from TikTok users, our study found that a user's illusion of intimacy with a micro-influencer (i.e., para-social interaction) had significant positive impact on the intention to participate in a hashtag challenge. This study also showed that the degree of para-social interaction in a short-form video platform was determined by both media content-related factors and media character-related factors (i.e., content attractiveness, physical attractiveness, and attitude homophily). Our work in this study provided significant theoretical and practical implications on how to leverage micro-influencers for the success of hashtag challenges in a short-form video platform.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2485-2487
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• 2015

Recently, Hashtag is widely used in SNS like Facebook, Twitter and personal blogs. However, the efficiency of tag search system is poor due to the indiscriminate use of hashtags. To enhance the accuracy of tag search system, we proposed a tag search system using the keyword extraction and similarity evaluation. The experimental results show that the proposed system provides the higher accuracy on tag search results.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.272-283
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• 2020

Hashtags (#) have received a great deal of attention from academia and industry as an effective digital tool for engaging social media users and facilitating electronic word-of-mouth for brands. We delved into motivations concerning people's brand-related hashtag-posting behavior on social media. The findings revealed three motivations for posting brand-related hashtags on social media: social acceptance, brand altruism, and incentive seeking. Additionally, we examined the relationships between motivations and brand relationship variables. The results showed that social acceptance and brand-related altruism predicted all of the five relationship variables (i.e., brand attitude, brand trust, brand affective and calculative commitment and brand loyalty), while incentive-seeking predicted brand calculative commitment and brand loyalty. The findings of the study provide some meaningful insights into the development of brand communication strategies and help marketers capitalize on social media platforms to achieve higher user involvement.

• Asia Marketing Journal
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• v.22 no.3
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• pp.71-85
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• 2020

Social media has emerged as a major hub of engagement between brands and consumers in recent years, and allows user-generated content to serve as a powerful means of encouraging communication between the sides. However, it is challenging to negotiate user-generated content owing to its lack of structure and the enormous amount generated. This study focuses on the hashtag, a metadata tag that reflects customers' brand perception through social media platforms. Online users share their knowledge and impressions using a wide variety of hashtags. We examine hashtags that co-occur with particular branded hashtags on the social media platform, Instagram, to derive insights about brand perception. We apply text mining technology and network analysis to identify the perceptions of brand images among consumers on the site, where this helps distinguish among the diverse personalities of the brands. This study contributes to highlighting the value of hashtags in constructing brand personality in the context of online marketing.

• Journal of Internet Computing and Services
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• v.15 no.5
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• pp.63-72
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• 2014

Twitter has been a popular social media platform where people post short messages of 140 characters or less via the web. A hashtag is a word or acronym created by Twitter users to open a discussion about certain topics and issues that have a very high percentage of trending. Since the hashtag posts are sorted by time, not relevancy, people who firstly use Twitter have had difficulty understanding their context. In this paper, we propose a HBase-based automatic summary system in order to reduce the difficulty of understanding. The proposed system combines an automatic summary method with a fuzzy system after storing the streaming data provided by Twitter API to the HBase. Throughout this procedure, we have eliminated the duplicate of contents in the hashtag posts and have computed scores between posts so that the users can access to the trending topics with relevancy.

• Journal of Fashion Business
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• v.27 no.3
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• pp.132-149
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• 2023

This study aims to analyze Instagram hashtags based on big data to investigate changes in consumer trends and perceptions of vegan fashion, and to derive strategies for revitalizing vegan fashion brands based on derived results. Among social media, Instagram was selected as a collection channel, and Instagram hashtags for 'Vegan Fashion' were collected from July 1, 2021 to December 31, 2021. After conducting semantic network analysis with the Ucinet 6 program based on the collected data, the CONCOR analysis on vegan fashion showed the following four clusters: 'Veganism practiced with fashion', 'Bag type of vegan fashion brand', 'Sharing vegan fashion', and 'Diversification of eco-friendly products'. Analysis results showed that the Instagram hashtag for vegan fashion confirmed the MZ generation's increased interest in vegan fashion and their thoughts to recommend and share frequently used items or brand products to people around them. CONCOR analysis of vegan fashion brands showed the following four groups: 'Differentiating the material of vegan bags', 'Eco-friendly products of vegan fashion brands', 'Interest in vegan shoes', and 'Donation campaign of vegan fashion brands'. CONCOR analysis on Meaningout showed the following four clusters: 'MZ Generation's Meaningout Start-up', 'Recommendation Platform for Skin Products', 'Value Consumption Trend for Eco-friendly Clothing', and 'Interest in Eco-friendly Packaging'. The results of this study on vegan fashion, a practical eco-friendly movement that can require changes in social responsibility and perception as issues that directly affect animals, the environment, and humans, are expected to provide basic data to help domestic vegan fashion brands develop marketing strategies.