• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.93-98
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• 2023

Instagram is one of the fastest-growing online photo social web services where users share their life images and videos with other users. Image tagging is an essential step for developing Automatic Image Annotation (AIA) methods that are based on the learning by example paradigm. Hashtags can be used on just about any social media platform, but they're most popular on Twitter and Instagram. Using hashtags is essentially a way to group together conversations or content around a certain topic, making it easy for people to find content that interests them. Practically on average, 20% of the Instagram hashtags are related to the actual visual content of the image they accompany, i.e., they are descriptive hashtags, while there are many irrelevant hashtags, i.e., stophashtags, that are used across totally different images just for gathering clicks and for search ability enhancement. Hence in this work, Sorting instagram hashtags all the way through mass tagging using HITS (Hyperlink-Induced Topic Search) algorithm is presented. The hashtags can sorted to several groups according to Jensen-Shannon divergence between any two hashtags. This approach provides an effective and consistent way for finding pairs of Instagram images and hashtags, which lead to representative and noise-free training sets for content-based image retrieval. The HITS algorithm is first used to rank the annotators in terms of their effectiveness in the crowd tagging task and then to identify the right hashtags per image.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.49-56
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• 2019

The purpose of this study is to analyze the characteristics and meanings of Instagram hashtags related to the exhibitions as a online communication platform of museums. At the same time, it focuses on efficiency of hashtags as a reference framework of inferring viewing experiences. We collect and visualize Instagram hashtags of exhibitions held in Korea for the past two years including 'Paper Present (2017)', 'YOUTH (2017)', 'Monet, Draw Light Exhibition (2018)', 'Van Gogh Inside (2016)', 'Drawn by the Wind: Shin yun-bok & Jeong Seon'. To sum up, significant data related to viewing experiences are not derived, and hashtags as a reference framework of inferring viewing experiences are turned out to be inefficient. Meanwhile, we conclude that potential for distributing information about the exhibitions is inherent in hashtags. In terms of informational characteristics, we notice that the influence of hashtags related to regional information is presented more than the response toward the viewing experiences. This result shows that Instagram users in the exhibitions are worthy of place making rather than viewing experiences.

• 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 Fashion Business
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• v.19 no.6
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• pp.112-126
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• 2015

In social environments, hashtags have been widely adopted and have become a new form of language for users. The current study attempts to enhance our understanding of users and their motivations to use hashtags when posting fashion-related information. Specifically, this study examines whether user characteristics (fashion leadership, conspicuousness) influence their motivations to use hashtags (curation, self-presentation, information diffusion), which then leads to behavioral intentions to continue to use hashtags and recommend the same to others. An online survey was administered to test our research questions. A total of 136 consumers in their 20s, 30s, and 40s living in Korea were used for data analysis. Structural equation modeling was conducted, which revealed that fashion leadership and conspicuousness had a positive impact on users' motivations of curation, self-presentation, and information diffusion. Motivations of self-presentation and information diffusions were found to affect users' behavioral intentions while curation had no significant impact. Practical implications are presented.

• Journal of The Geomorphological Association of Korea
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• v.24 no.1
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• pp.93-104
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• 2017

The objective of this study was two fold: firstly, we analyzed how the Geoparks have been run since the first one had been designated on December 31th, 2015. We then investigated how visitors' geographical and geological recognitions on the parks have changes. We visited geosites and investigated how well these sites accorded with the conditions for running Geoparks. In addition, scenery pictures and hashtags uploaded in Instagram between 2015 and 2016 were collected in order to analyze visitors preferences on the geosites along the, Hantan Imjingang River Geopark. Results showed that the hotspots were Bidulginang Waterall, Art Valley, and Jaein Waterfall. Compared to the ratio of geographical and geological references in 2015, the hashtags in all of these three geosites increased. The increases were as much as 3% in Bidulginang Falls, 0.6% in Art Valley, and 5% in Jaein Falls. In labelling the geographical and geological terms in Bidulginang Falls and Jaein Falls, the most frequently mentioned hashtags was "columnar joint", followed by "natural monument", "Geopark", and "basalt canyon". This study includes the study of visitors recognition which is one of the most important, but somehow neglected factor for the geopark's management.

• 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.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.284-291
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• 2022

People use various tools to present themselves including Social Network Services(SNS hereafter). This study categorized three types of presentation of self, which are genuine, ideal, and social self, and based on Goffman's Impression Management Framework, investigated if these types of presentations have any patterns related to SNS posting styles. Especially, we focused on the styles of hashtags including if hashtags are used in the main tests, if hashtags are hidden, and what kinds of words are used for hashtags. Using 450 posting data uploaded to the Instagram, we found that the posting presenting ideal self show very high rate of using hidden hashtags(98%) and using common expressions(97%), which are not the case for genuine and social self types. This results imply that people concern more about their impressions especially when they present their ideal self on SNS, partially confirming Goffman's Impression Management Framework.

• Journal of Korea Multimedia Society
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• v.23 no.8
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• pp.1049-1058
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• 2020

'Instagrammable' is a new term which means a photo or a series of pictures are worth posting on Instagram. Since Instagram is an image-oriented social media platform, it is important to give users proper awareness through images in order to be an instagrammable post. In this study, we explored the proper delivery method of messages within instagrammable posts through the use of hashtags(#). Specifically, we paid attention to the use of 'Card News', which involves a series of images that form a short narrative. Hashtags play an important role that they often describe sharing intention of the post, and we found analyzing the use of hashtags in Card News posts is a good indicator of users' Instagram activities. Currently, there are more than 580k posts are found with the search keyword Card News, and the number is increasing. In this study, we collected and analyzed more than 50k hashtags on Instagram to explore how news stories are posted from both the general users and news media accounts. Furthermore, we conducted interviews with journalists to analyze how news media are making use of Instagram as a legitimate place to share news stories with impact.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.179-180
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• 2019

Nowadays, clustering algorithm is considered as a promising solution for lacking human-labeled and massive data of social media sites in numerous machine learning tasks. Many researchers propose disaster event detection systems have ability to determine special local events, such as missing people, public transport damage by clustering similar tweets and hashtags together. In this paper, we try to extend tweet hashtag feature definition by applying word embedding. The experimental results are described that word embedding achieve better performance than the reference method.