• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.83-88
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• 2024

In this paper we used classification algorithms on social networking. We are proposing, a new classification algorithm called the improved Decision Tree (IDT). Our model provides better classification accuracy than the existing systems for classifying the social network data. Here we examined the performance of some familiar classification algorithms regarding their accuracy with our proposed algorithm. We used Support Vector Machines, Naïve Bayes, k-Nearest Neighbors, decision tree in our research and performed analyses on social media dataset. Matlab is used for performing experiments. The result shows that the proposed algorithm achieves the best results with an accuracy of 84.66%.

• Information Systems Review
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• v.21 no.2
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• pp.29-50
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• 2019

Social media is divided into Owned Media, operated by companies according to information sources, and Earned Media, which third parties produce contents. Social media research developing the logic that brand-related content in social media increases awareness of potential customers and positively changes brand attitudes, resulting in increased sales and business performance. However, there are limitations in previous researches that can not fully explain the difference of media synergy effect according to the information source of social media. it is very important for the consumer to integrate media management because consumers are more likely to choose appropriate media information for the information needed at each decision making stage. The purpose of this study is to analyze the effect of eWOM of review site and social media (owned media and earned media) on movie sales. To do this, we collected 3,589 review data from films released in 2017. The results of the study showed that eWOM of review site, social media (owned media and earned media) had a positive effect on movie sales. However, it was found that the effect of moderating eWOM of review site was different between the owned media and the earend media.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.1-7
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• 2023

Since the first outbreak of COVID-19 in 2019, it has caused a huge blow to the restaurant industry. However, as social distancing was lifted as of April 2022, the restaurant industry gradually recovered, and as a result, interest in restaurant start-ups increased. Therefore, in this paper, big data analysis was conducted by selecting "restaurant start-up" as a key keyword through social media big data analysis using Textom and then conducting word frequency and CONCOR analysis. The collection period of keywords was selected from May 1, 2022 to May 23, 2023, after the lifting of social distancing due to COVID-19, and based on the analysis, the development of a restaurant start-up consulting chatbot service is proposed.

• Science of Emotion and Sensibility
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• v.26 no.4
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• pp.3-14
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• 2023

Recently, the effect of using social media on psychological well-being has been highlighted. However, studies exploring factors that may predict the quality of social media relationships are relatively rare. The present study investigated whether social media activity and psychological states, such as loneliness and depression, can predict the quality of social media relationships during the COVID-19 quarantine period using a machine learning technique. Ninety-five participants completed a self-report survey on loneliness, Instagram activity, quality of social media relationships, and depression at different time points (during the self-isolation and after the release of self-isolation). Similarity analyses, including multidimensional scaling (MDS), representational similarity analysis (RSA), and classification analyses, were conducted separately at each point in time. The results of MDS revealed that time spent on social media and depression were distinguished from others in the first dimension, and loneliness and passive use were distinguished from others in the second dimension. We divided the data into two groups based on the quality of social media relationships (high and low), and we conducted RSA on each group. Findings indicated an interaction between the quality of the social media relationships and the situation. Specifically, the effect of self-isolation on the high-quality social media relationship group is more pronounced than that on the low-quality group. The classification results also revealed that the predictors of social media relationships depend on whether or not they are isolated. Overall, the results of this study imply that social media relationship could be well predicted when people are not in isolated situations.

• Journal of the Korea Convergence Society
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• v.11 no.3
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• pp.201-210
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• 2020

The study was conducted to predict usage attitudes and behaviors by combining usage motivation and sensitivity, gender, and age in aviation-related social media. Specifically, the purpose of this study was to examine the effects of social media information acceptance, motivation and sensitivity on gender acceptance by gender and age. To this end, we collected data in an even distribution to prevent gender and age bias among adults aged 20 or older online from April 19 to May 3, 2018. As a result, the lower the female and age in the gender and age had a positive effect on the acceptance of social media information. Motivation for use has a positive effect on information acceptance and sensitivity has a negative effect on information acceptance. Through this, it was found that user class such as gender and age, motivation to use, and sensitivity affect information acceptance. In addition, the negative aspects of the sensitivity factor can be identified, and it is expected to be used as basic data in aviation-related social media marketing strategies.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.6
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• pp.457-464
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• 2020

This study aims to recognize customers' real sentiment and then discover the data-driven insights for strategic decision-making in the financial sector of Saudi Arabia. The data was collected from the social media (Facebook and Twitter) from start till October 2018 in financial companies (NCB, Al Rajhi, and Bupa) selected in the Kingdom of Saudi Arabia according to criteria. Then, it was analyzed using a sentiment analysis, one of data mining techniques. All three companies have similar likes and followers as they serve customers as B2B and B2C companies. In addition, for Al Rajhi no negative sentiment was detected in English posts, while it can be seen that Internet penetration of both banks are higher than BUPA, rarely mentioned in few hours. This study helps to predict the overall popularity as well as the perception or real mood of people by identifying the positive and negative feelings or emotions behind customers' social media posts or messages. This research presents meaningful insights in data-driven approaches using a specific data mining technique as a tool for corporate decision-making and forecasting. Understanding what the key issues are from customers' perspective, it becomes possible to develop a better data-based global strategies to create a sustainable competitive advantage.

• Journal of Information Science Theory and Practice
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• v.8 no.3
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• pp.6-14
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• 2020

On information markets, we can identify different relations between sellers and their customers, with some users paying with money, some paying with attention, and others paying with their personal data. For the description of these different market relations, this article introduces the notion of arity into the scientific discussion. On unary information markets, customers pay with their money; examples include commercial information suppliers. Binary information markets are characterized by one market side paying with attention (e.g., on the search engine Google) or with personal data (e.g., on most social media services) and the other market side (mainly advertisers) paying with money. Our example of a ternary market is a social media market with the additional market side of influencers. If customers buy on unary markets, they know what to pay (in terms of money). If they pay with attention or with their personal data, they do not know what they have to pay exactly in the end. On n-ary markets (n greater than 1), laws should regulate company's abuse of money and-which is new-abuse of data streams with the aid of competition (or anti-trust) laws, and by modified data protection laws, which are guided by fair use of end users' attention and data.

• International journal of advanced smart convergence
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• v.10 no.4
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• pp.134-140
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• 2021

Big data has recently been used in various industries such as tourism, medical care, distribution, and marketing. And it is evolving to the stage of collecting real-time information or analyzing correlations and predicting the future. In the tourism industry, big data can be used to identify the size and shape of the tourism market, and by building and utilizing a large-capacity database, it is possible to establish an efficient marketing strategy and provide customized tourism services for tourists. This paper has begun with anticipation of the effects that would occur when big data is actively used in the tourism field. Because the method of use must have applicability and practicality, the spatial scope will be limited to Seosan, Chungcheongnam-do, and research will be conducted. In this paper, to improve the quality of tourism courses by collecting and analyzing the number of mention data and sentiment index data on social media, which reflect the tourist's interest, preference and satisfaction. Therefore, it is used as basic data necessary for the development of new local tourism courses in the future. In addition, the development of tourism courses will be able to promote tourism growth and also revitalizing the local economy.

• The Journal of the Korea Contents Association
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• v.20 no.3
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• pp.515-526
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• 2020

Digital healthcare is a combined area of medical field and IT and various information on digital healthcare is provided in social media. This study aims to find the research trend of digital healthcare by collecting and analyzing data related to digital healthcare through the social media. The data were collected from Naver and Daum's news and blogs from January 2008 to June 2019. Major keywords with high frequency were extracted and visualized with wordcloud and network analysis was used to analyze the relationship between major keywords. Research combining medical field and IT from 2008 to 2001, various convergence research based on medical field and IT from 2012 to 2015, convergence research that applied the 4th industrial revolution technologies such as big data, blockchain and AI were actively conducted from 2016 to June 2019.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.169-175
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• 2023

This paper analyzes museum-related big data using museums and gamification using social media big data, identifies and compares the perceptions of visitors mentioned in social media, and presents ways to use gamification. Based on the collected data, this paper aims to provide data by comparing and analyzing the perception of visitors to the museum and visitors to the museum using gamification. This paper investigates the perception of visitors through social media analysis using TEXTOM, a social media analysis tool, to identify differences in perception. As a result of the analysis, it was found that compared to museums that were previously viewed in the form of exhibitions, they felt fun and interest in visiting museums using geikipication. In addition, based on the analysis results of keywords and related keywords, the perception, motivation, and type of viewing of the museum of the National Museum of Korea and the Independence Hall of Korea were confirmed. In addition, it can be seen that the sense of achievement of visitors who visited the museum using gamification is higher than that of the existing museum. It is believed that by developing and activating game-related content in future museum visits, many visitors will be able to increase their interest in the museum and feel fun and interested. The results of the study are believed to be meaningful as basic data to grasp the overall perception of visitors to the museum, and based on this, it is expected that visitors will be able to see and experience the museum in various ways.