• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.6
• /
• pp.309-314
• /
• 2017

In general, there are many difficulties in collecting, storing, and analyzing SNS (social network service) data, since those data have big data characteristics, which occurs very fast with the mixture form of structured and unstructured data. In this paper, we propose a new data visualization framework that works on Apache Storm, and it can be useful for real-time and dynamic analysis of SNS data. Apache Storm is a representative big data software platform that processes and analyzes real-time streaming data in the distributed environment. Using Storm, in this paper we collect and aggregate the real-time Twitter data and dynamically visualize the aggregated results through the tag cloud. In addition to Storm-based collection and aggregation functionalities, we also design and implement a Web interface that a user gives his/her interesting keywords and confirms the visualization result of tag cloud related to the given keywords. We finally empirically show that this study makes users be able to intuitively figure out the change of the interested subject on SNS data and the visualized results be applied to many other services such as thematic trend analysis, product recommendation, and customer needs identification.

• Spatial Information Research
• /
• v.22 no.4
• /
• pp.21-38
• /
• 2014

Since users who search maps conduct their searching using the name they already know or is commonly called rather than formal name of a specific place, they tend to fail to find their destination. In addition, in typical web map service in terms of spatial searching of map. Location information of unintended place can be provided because when spatial searching is conducted with the vocabulary 'nearby' and 'in the vicinity', location exceeding 2 km from the current location is searched altogether as well. In this research, spatial range that human can perceive is calculated by extracting POI date with the usage of twitter data of SNS, constructing spatial relations with existing POI, which is already constructed. As a result, various place names acquired could be utilized as different names of existing POI data and it is expected that new POI data would contribute to select places for constructing POI data by utilizing to recognize places having lots of POI variation. Besides, we also expect efficient spatial searching be conducted using diverse spatial vocabulary which can be used in spatial searching and spatial range that human can perceive.

• Journal of KIISE
• /
• v.42 no.3
• /
• pp.390-398
• /
• 2015

Spatial web objects refer to web documents that contain geographic information. Recently, services that create spatial web objects have increased greatly because of the advancements in devices such as smartphones. For services such as Twitter or Facebook, simple texts posted by users is stored along with information about the post's location. To search for such spatial web objects, a method that uses spatial information and text information simultaneously is required. Conventional spatial web object search methods mostly use R-tree and inverted file methods. However, these methods have a disadvantage of requiring a large volume of space when building indices. Furthermore, such methods are efficient for searching with many keywords but are inefficient for searching with a few keywords.. In this paper, we propose a spatial web object search method that uses a quad-tree and a patricia-trie. We show that the proposed technique is more effective than existing ones in searching with a small number of keywords. Furthermore, we show through an experiment that the space required by the proposed technique is much smaller than that required by existing ones.

• Journal of the Korean Society for information Management
• /
• v.27 no.3
• /
• pp.35-51
• /
• 2010

Emerging Web 2.0 services such as Twitter, Blogs, and Wikis alongside the poorlystructured and immeasurable growth of information requires an enhanced information organization approach. Ontology has received much attention over the last 10 years as an emerging approach for enhancing information organization. However, there is little penetration into current systems. The purpose of this study is to propose ontology implementation and methodology. To achieve the goal of this study, limitations of traditional information organization approaches are addressed and emerging information organization approaches are presented. Two ontology data models, RDF/OW and Topic Maps, are compared and then ontology development processes and methodology with topic maps based medical information retrieval system are addressed. The comparison of two data models allows users to choose the right model for ontology development.

• Knowledge Management Research
• /
• v.15 no.3
• /
• pp.37-66
• /
• 2014

Since social network service (SNS) has been widely used as a effective way for people to connect and communication with each other, the use of corporate SNS account also has increased. However, compared to a private SNS account, only few people have a continuous relationship with their corporate SNS account because the use of corporate SNS account tends to be one-time and temporary activity whenever the users just need events and information. Given the psychological side effects of using SNS, the relative lack of empirical studies on the impacts of emotional factor in SNS prevents the deeper understanding of the intention to continuous using corporate SNS account. Therefore, this study aims to explore key determinants of the intension to continuous using the corporate SNS account from a habit and emotional perspective. To bridge research gap, we attempt to divide emotional factor into the following 5 factors based on Mehrabian and Russell model (1974): intimacy, enjoyment (positive factor), privacy concern, anxiety (negative factor), arousal (arousal factor) and (dominant factor). The basic model is proposed to explore the effects of habit and emotional factors on the intension to continuous using the corporate SNS account. We then examine how the effects of habit and emotional factors differ depending on social media types (e.g., facebook and twitter). The results indicates that habit is related to emotional factors, and each emotional factor differently influences the intension to continuous using the corporate SNS account. The results also confirm that the effects of the habit and emotional factors on the intension to continuous using the corporate SNS account differ according to social media types. This study provides practical and useful guidance and the strategic marketing insight for managers in maintaining and improving the intension to continuous using the corporate SNS account.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.14 no.6
• /
• pp.7-12
• /
• 2014

It has good features for social networking with friends SNS is maintained. However, various enterprises, individuals invading the inconvenience spammers have exposure to a number of users to tweet spam. The study was conducted in the existing research on these spam tweets. However, the results showed a more accurate classification and detection is difficult because of the lack of precision and different causes. In this paper, we describe how to classify the characteristics of spammers, classification criteria. Also has a link rate and difference between followers and following, these features were present classification criteria for spammers account. This experiment was performed according to the criteria. Randomized trial of spam and non-spam accounts were selected and account type was conducted according to the criteria 68% of the link ratio of spam accounts. Followers / Following ratio was 27581.5. Non-spam accounts was 6.12%. Followers / Following ratio was 1.26.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.24 no.3
• /
• pp.292-297
• /
• 2014

As a Social Network Service (SNS) has become an integral part of our everyday lives, millions of users can express their opinion and share information regardless of time and place. Hence sentiment analysis using micro-blogs has been studied in various field to know people's opinion on particular topics. Most of previous researches on movie reviews consider only positive and negative sentiment and use it to predict movie rating. As people feel not only positive and negative but also various emotion, the sentiment that people feel while watching a movie need to be classified in more detail to extract more information than personal preference. We measure sentiment distributions of each movie from tweets according to the Thayer's model. Then, we find similar movies by calculating similarity between each sentiment distributions. Through the experiments, we verify that our method using micro-blogs performs better than using only genre information of movies.

• Journal of Internet Computing and Services
• /
• v.17 no.2
• /
• pp.87-95
• /
• 2016

Considerable research over the years has been devoted to ascertaining the impact of social media on political settings.In recent days, Social Network Sites (SNS) such as Facebook allowed users to share their political beliefs, support specific candidates, and interact with others on political issues. This study examines the role of SNS as the means of political campaign. The study tasks the case of the 2015'sspecial election, Seoul Korea. The analysis aims to identify how candidates use Facebook or Twitter to interact with voters by applying functional theory of political campaign discourse developed by Benoit. In this study, we analyzed the candidates' SNS messages in terms of political behavior such as self-expression, informing policy, asking voters to participate in political events. Among them the results indicated that two candidates, Jung, Dong Young and Byun, Hee Jae, both of them used SNS to express themselves the most. The study also found that two candidates used mainly the strategy called 'acclaim' which praises their own strengths. In terms of topics of SNS messages (policy versus character) there was different between two candidates. Jung, sent message in relation to 'character' the most, while Byun contained 'policy' message on SNS the most. Based on these findings implications and directions for future studies are discussed.

• The Journal of the Convergence on Culture Technology
• /
• v.6 no.2
• /
• pp.449-454
• /
• 2020

This paper proposes a machine learning-based emotion analysis system that detects a user's depression through their SNS posts. We first made a list of keywords related to depression in Korean, then used these to create a training data by crawling Twitter data - 1,297 positive and 1,032 negative tweets in total. Lastly, to identify the best machine learning model for text-based depression detection purposes, we compared RNN, LSTM, and GRU in terms of performance. Our experiment results verified that the GRU model had the accuracy of 92.2%, which is 2~4% higher than other models. We expect that the finding of this paper can be used to prevent depression by analyzing the users' SNS posts.

• The Journal of Information Systems
• /
• v.23 no.1
• /
• pp.73-91
• /
• 2014

Microblog is emerging as a new communication service because of its usefulness and real-time accessability. Recently, microblog services, such as twitter and me2day in Korea, are getting a great attention. Continuous use intention is critical to sustain the service. However, most recent studies are based on Technology Acceptance Model(TAM) and Expectation Confirmation Model(ECM). These models are only focused on individual factors and overlook social influence factors. Social influence has been indicated as a critical factor of technology adoption and diffusion in social context(Davis, 1989; Fulk et al., 1987). In this study, we explore factors related to social influence which effect on continuous use intention for 'me2day' that is one of the most famous microblog in Korea. The purpose of this study is to understand continuous use intention and examine the relationship among social influence factors, social presence, and continuous use intention. To understand the phenomenon of continuous use intention in microblog service, this study employed social influence theory and expanded it by adding personal network exposure and group norm as additional social influence factors. The results show that social identity, group norms, and social presence positively influences continuous use intention. Contrary to our expectation, personal network exposure does not influence on continuous use intention. Academically, this research can contribute to microblog research field through elucidating the relationship among social influence factors, social presence, and continuous use intention. Although there is not enough research which is considered social influence factors as major explanation for continuous use intention, this study can give novel point of view to understand continuous use intention of microblog. Practically, service providers could consider ways to encourage users to continually use microblog service by reinforcing social influence factors and social presence.