Facebook, which has the largest number of users worldwide, has both positive and negative effects on our lives and society. The positive effects include social support from others, relationship building, entertainment, etc. In contrast, Facebook users also experience negative emotions such as tiredness and irritation, resulting in dissatisfaction as well as withdrawal from Facebook. The current study investigates both positive and negative effects of the use of by different demographic characteristics (i.e., age and gender), Facebook usage pattern (i.e., posters vs. lurkers), and Facebook usage time and frequency. The results show that (1) female users (vs. male users) feel higher level of fatigue and display stronger intention to discontinue Facebook. Moreover, (2) posters (vs. lurkers) feel higher level of positive emotions and social support, and stronger intention to continue Facebook. Lastly, (3) heavy users (vs. light users) exhibit higher level of positive emotions and stronger intentions to continue Facebook. This research sheds light on the fact that the characteristics of users affect individuals' intention to discontinue SNS and offers practical implications on the ever-expanding SNS market.
The biggest characteristic of Social Network Game(SNG) is that games are played through competition and cooperation with the actual acquaintances based on SNS. Even though such competition and challenge spirit have been dealt importantly as preceding factors having influence on the flow in games in the existing game area, it is rare to find researches deeply considering the characteristics of ranking competition between acquaintances in SNG. Moreover, it was not considered that such acquaintances could be the targets of competition and also challenge at the same time in SNG. Therefore, this study examined the achievements(big differences in ranking, small differences in ranking) of the targets for comparison and closeness(strong ties, weak ties) with the targets for comparison as factors having influence on competition and challenge spirit, and also empirically analyzed the influence of such factors and interactions between factors on players' competition and challenge spirit in the ranking competitive society, by analyzing the characteristics of ranking competition between acquaintances in the mobile puzzle, SNG based on SNS through the analysis on the preceding research on the self-evaluation maintenance model of the social comparison theory. In the results, when preferentially exposing competitors with small difference in ranking and also exposing competitors with stronger ties, players' competition is stimulated, so that it can improve their challenge spirit. Such results of this study can be expected to a lot contribute to the actual design work of SNG ranking table contents.
Journal of Korean Society for Geospatial Information Science
/
v.24
no.1
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pp.25-33
/
2016
In order to visualize point based Location-Based Social Network Services(LBSNS) data on multi-scaled tile map effectively, it is necessary to apply tile-based clustering method. Then determinating reasonable numbers and size of tiles is required. However, there is no such criteria and the numbers and size of tiles are modified based on data type and the purpose of analysis. In other words, researchers' subjectivity is always involved in this type of study. This is when Modifiable Areal Unit Problem(MAUP) occurs, that affects the results of analysis. Among LBSNS, geotagged Twitter data were chosen to find the influence of MAUP in scale effects perspective. For this purpose, the degree of spatial autocorrelation using spatial error model was altered, and change of distributions was analyzed using Morna's I. As a result, positive spatial autocorrelation showed in the original data and the spatial autocorrelation was decreased as the value of spatial autoregressive coefficient was increasing. Therefore, the intensity of the spatial autocorrelation of Twitter data was adjusted to five levels, and for each level, nine different size of grid was created. For each level and different grid sizes, Moran's I was calculated. It was found that the spatial autocorrelation was increased when the aggregation level was being increased and decreased in a certainpoint. Another tendency was found that the scale effect of MAUP was decreased when the spatial autocorrelation was high.
Journal of the Korea Institute of Information Security & Cryptology
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v.26
no.5
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pp.1235-1241
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2016
Personalized App recommendation system is recently famous since the number of various apps that can be used in smart phones that increases exponentially. However, the site users using google play site with malwares have experienced severe damages of privacy exposure and extortion as well as a simple damage of satisfaction descent at the same time. In addition, Sybil attack (Sybil) manipulating the score (rating) of each app with falmay also present because of the social networks development. Up until now, the sybil detection studies and malicious apps studies have been conducted independently. But it is important to determine finally the existence of intelligent attack with Sybil and malware simultaneously when we consider the intelligent attack types in real-time. Therefore, in this paper we experimentally evaluate the relationship between malware and sybils based on real cralwed dataset of goodlplay. Through the extensive evaluations, the correlation between malware and sybils is low for malware providers to hide themselves from Anti-Virus (AV).
This exploratory study aims to review the risks and threats of social network services(SNSs), particularly focusing upon the policing perspective. This paper seeks to acknowledge the present risk/danger of SNSs and the very significance of establishing a strategic framework to effectively prevent and/or control criminal misuse of SNSs. This research thus advocates that proactive study on security issues and criminal aspects of SNSs and preventive countermeasures can play a significant role in policing the networked society in the time of digital/internet age. Social network sites have been increasingly attracting the attention of entrepreneurs, and academic researchers as well. In this exploratory article, the researcher tried to define concepts and features of SNSs and describe a variety of issues and threats posed by SNSs. After summarizing existing security risks, the researcher also investigated both the potential threats to privacy associated with SNSs, such as ID theft and fraud, and the very danger of SNSs in case of being utilized by terrorists and/or criminals, including cyber-criminals. In this study, the researcher primarily used literature reviews and empirical methods. The researcher thus conducted extensive case studies and literature reviews on SNSs. The literature reviews herein cover theoretical discussions on characteristics, usefulness, and/or potential danger/harm of SNSs. Through the literature review, the researcher also concentrated upon being able to identify a strategic framework for law enforcement to effectively prevent criminal misuse of SNSs The limitation of this study can be lack of statistical data and attempts to examine previously un-researched area in the field of SNS and its security risks and potential criminal misuse. Thus, to supplement this exploratory study, more objective theoretical models and/or statistical approaches would be needed to provide law enforcement with sustainable policing framework and contribute to suggesting policy implications.
Purpose - The objective of this study is to investigate the dynamic relationships among Advertising Cost (AD), Newly Registered Users(NRU), and Buying Users(BU) of Social Network Game(SNG). SNG is getting pervasive mainly due to the rapid growth of mobile game and Social Network Service(SNS). It would be helpful for marketing researchers interested in SNG and related practitioners to understand the changes in AD, NRU, and BU with time as well as the effects on one another in mutual and dynamic way. Research Design, Data, and Methodology - Necessary data were collected from Social Network Game(SNG) company. AD, NRU, and BU are endogenous variables, but new event such as launching (event) and holidays(holiday) are exogenous dummy variables. Vector Auto regression (VAR) model is generally used to examine and capture the dynamic relationships among endogenous variables. VAR model can easily capture dynamic and endogenous relationships among time-series variables. Vector Auto regression with Exogenous variables(VARX) is a model in which exogenous variables are added to VAR. To investigate this study, VARX is applied. Result - By estimating the VARX model, the author finds that the past periods' NRU affect negatively and significantly the present AD, and past periods' BU have a positive and significant impact on the increase of AD. In addition, the author shows that the past periods' AD and BU have a positive and significant effect on the increase of NRU, and the past periods' AD affect positively and significantly BU. While the impact of AD on NRU happens after 3 or 4 days (carryover effect), that of AD on BU comes about within just 1 or 2 days (immediate effect). The effect of BU on NRU can be considered as word of mouth (WOM effect). Therefore, SNG companies can obtain not only the growth of revenue but also the increase of NRU by increasing BU. Through those results, the author can also find that there are significant interactions between endogenous variables. Conclusion - This study intends to investigate endogenous and dynamic relationships between AD, NRU, and BU. They also give managerial implications to practitioners for SNS and SNG firms. Through this study, it is found that there exist significant interactions and dynamic relationships between those three endogenous variables. The results of this study can have meaningful implications for practitioners and researchers of SNG. This research is unique in that it deals with "actual" field data and intend to find "actual" relationships among variables unlike other related existing studies which intend to investigate psychological factors affecting the intention of game usage and the intention of purchasing game items. This study is also meaningful by showing that the increase of BU can be a good strategy for "killing birds with one stone" (i.e., revenue growth and NRU increase). Although there are some limitations related with future research topics, this research contributes to the current research on SNG marketing in the above mentioned ways.
KIPS Transactions on Software and Data Engineering
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v.4
no.10
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pp.447-454
/
2015
This paper proposes geographical name denoising by machine learning of event detection based on twitter. Recently, the increasing number of smart phone users are leading the growing user of SNS. Especially, the functions of short message (less than 140 words) and follow service make twitter has the power of conveying and diffusing the information more quickly. These characteristics and mobile optimised feature make twitter has fast information conveying speed, which can play a role of conveying disasters or events. Related research used the individuals of twitter user as the sensor of event detection to detect events that occur in reality. This research employed geographical name as the keyword by using the characteristic that an event occurs in a specific place. However, it ignored the denoising of relationship between geographical name and homograph, it became an important factor to lower the accuracy of event detection. In this paper, we used removing and forecasting, these two method to applied denoising technique. First after processing the filtering step by using noise related database building, we have determined the existence of geographical name by using the Naive Bayesian classification. Finally by using the experimental data, we earned the probability value of machine learning. On the basis of forecast technique which is proposed in this paper, the reliability of the need for denoising technique has turned out to be 89.6%.
Journal of the Korean BIBLIA Society for library and Information Science
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v.22
no.3
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pp.75-90
/
2011
This study aimed to investigate, analyze and identify the problems related to SNS usage by publishing companies around Twitter, Facebook and Me2day as well as theoretically investigate SNS, and ultimately to suggest the approaches to improve the outstanding issues identified. In accordance with the analysis, only 0.5%(222 publishing companies) in total publishing companies(41,407) opened SNS[3.7%(1,537) opened the independent website.] Second, in accordance with the investigation on 212 publishing companies in 222 companies opening SNS(71 twitters, 74 facebooks, 67 Me2days), the communication was not significant to the extent that only 50.5%(107) kept the communication with less than 100 readers or potential readers. Furthermore, 77.4%(164 companies) had less than 1,000 postings by publishing companies. The analysis on the postings(500) by users and postings(300) by publishing companies demonstrated that those postings were mostly related to marketing, introduction, recommendation and reading of publications by publishing companies. It means that the postings were mostly positive. However, 86.6% of postings by users in SNS of publishing companies was merely one-time posting. It indicated that continuity was not sufficient.
Public awareness of alien species can vary by generation, period, or specific events associated with these species. An understanding of public awareness is important for the management of alien species because differences in public awareness can affect the establishment and implementation of management plans. We analyzed digital texts on social media platforms, news articles, and internet search volumes used in conservation culturomics to understand public interest and sentiment regarding alien freshwater species. The number of tweets, number of news articles, and relative search volume to 11 freshwater alien species were extracted to determine public interest. Additionally, the trend over time, seasonal variability, and repetition period of these data were confirmed. We also calculated the sentiment score and analyzed public sentiment in the collected data using sentiment analysis based on text mining techniques. The American bullfrog, nutria, bluegill, and largemouth bass drew relatively more public interest than other species. Some species showed repeated patterns in the number of Twitter posts, media coverage, and internet searches found according to the specified periods. The text mining analysis results showed negative sentiments from most people regarding alien freshwater species. Particularly, negative sentiments increased over the years after alien species were designated as ecologically disturbing species.
This study aims to understand the thematic trends globally developed in the 'Green Urbanism' related research. Research methodology is based on systemic review of international literature published for the past 20 years period between 2000 and 2020. The specific methods applied include not only literature search by citation, co-authorship, and co-occurrence but social network analysis in order to find correlations among the publication. The correlations are visualized and analysed using VOSviewer and Ucinet software. The analysis indicates that total of 51 studies were carried out by 89 authors from 54 institutions across 21 countries during the period. The majority of the research was done by a country-specific study and only a few research were collaborative studies with other countries. The most common theme that occurred in the early years was 'sustainability and the theme evolved toward specific ones such as 'built environment', 'infrastructure', and 'health'. Having considered that climate change has become a global challenge, green urbanism is expected to be a future direction to pursue environmentally sustainable urban spaces. This study also implies that governance, policy support, and intervention are crucial factors in developing sustainable urban spaces.
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