Pub Date : 2013-09-08DOI: 10.1109/SocialCom.2013.123
Shih-Hong Jheng, Cheng-te Li, Hsi-Lin Chen, M. Shan
Microblogging services such as Twitter and Plurk allow users to easily access and share different types of social multimedia (e.g. images and videos) over the online social world. However, information overload happens to users and prohibits them from reaching popular and important digital contents. This paper studies the problem of predicting the popularity of social multimedia which is embedded in short messages of microblogging social networks. Social multimedia exhibits the property that they might be persistently or periodically re-shared and thus their popularity might resurrect at some time and evolve over time. We exploit the idea of concept drift to capture this property. We formulate the problem using classification, and propose to tackle the tasks of Re-share classification and Popularity Score classification. Two categories of features are devised and extracted, including information diffusion and explicit multimedia meta information. We develop a concept drift-based popularity predictor, by ensembling multiple trained classifiers from social multimedia instances in different time intervals. The key lies in dynamically determining the ensemble weights of classifiers. Experiments conducted on the Plurk data show the high accuracy on the popularity classification and the promising results on detecting popular social multimedia.
{"title":"Popularity Prediction of Social Multimedia Based on Concept Drift","authors":"Shih-Hong Jheng, Cheng-te Li, Hsi-Lin Chen, M. Shan","doi":"10.1109/SocialCom.2013.123","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.123","url":null,"abstract":"Microblogging services such as Twitter and Plurk allow users to easily access and share different types of social multimedia (e.g. images and videos) over the online social world. However, information overload happens to users and prohibits them from reaching popular and important digital contents. This paper studies the problem of predicting the popularity of social multimedia which is embedded in short messages of microblogging social networks. Social multimedia exhibits the property that they might be persistently or periodically re-shared and thus their popularity might resurrect at some time and evolve over time. We exploit the idea of concept drift to capture this property. We formulate the problem using classification, and propose to tackle the tasks of Re-share classification and Popularity Score classification. Two categories of features are devised and extracted, including information diffusion and explicit multimedia meta information. We develop a concept drift-based popularity predictor, by ensembling multiple trained classifiers from social multimedia instances in different time intervals. The key lies in dynamically determining the ensemble weights of classifiers. Experiments conducted on the Plurk data show the high accuracy on the popularity classification and the promising results on detecting popular social multimedia.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116109333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-08DOI: 10.1109/SocialCom.2013.47
Piraveenan Mahendra, M. S. Uddin, Gnana Thedchanamoorthy
It is well known that non-vaccinated individuals may be protected from contacting a disease by vaccinated individuals in a social network through community protection (herd immunity). Such protection greatly depends on the underlying topology of the social network, and the strategy used in selecting individuals for vaccination. Social networks however undergo constant growth, and it may be argued that network growth may change the level of herd immunity present in social networks. In this paper, we analyse the effect of growth and immunization strategies on herd immunity of social networks. Considering three classical topologies - Random, scale-free and small-world, we compare the influence of immunization strategies on each of them and then discuss how network growth can nullify or amplify these differences. We show that betweenness based vaccination is best strategy of immunization, regardless of topology, in static networks, but its prominence over other strategies diminishes in dynamically growing topologies. We demonstrate that herd immunity of random networks actually increases with growth, if the proportion of survivors to a secondary infection is considered, while the community protection in scale-free and small world networks decreases with growth. We compare the relative influence of growth on each class of networks vaccinated under different strategies.
{"title":"Effect of Vaccination Strategies on the Herd Immunity of Growing Networks","authors":"Piraveenan Mahendra, M. S. Uddin, Gnana Thedchanamoorthy","doi":"10.1109/SocialCom.2013.47","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.47","url":null,"abstract":"It is well known that non-vaccinated individuals may be protected from contacting a disease by vaccinated individuals in a social network through community protection (herd immunity). Such protection greatly depends on the underlying topology of the social network, and the strategy used in selecting individuals for vaccination. Social networks however undergo constant growth, and it may be argued that network growth may change the level of herd immunity present in social networks. In this paper, we analyse the effect of growth and immunization strategies on herd immunity of social networks. Considering three classical topologies - Random, scale-free and small-world, we compare the influence of immunization strategies on each of them and then discuss how network growth can nullify or amplify these differences. We show that betweenness based vaccination is best strategy of immunization, regardless of topology, in static networks, but its prominence over other strategies diminishes in dynamically growing topologies. We demonstrate that herd immunity of random networks actually increases with growth, if the proportion of survivors to a secondary infection is considered, while the community protection in scale-free and small world networks decreases with growth. We compare the relative influence of growth on each class of networks vaccinated under different strategies.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116903532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-08DOI: 10.1109/SocialCom.2013.128
Ahmad Albu-Shamah, J. Zhan
Obesity is simply defined as the condition of being significantly overweight. It's the state where an individual weight is greater than and exceeding the healthy weight. Obesity and overweight has become the fastest growing epidemic affecting not only Americans but also the entire population in the world. Now, The question is how to fight Obesity? Surely there are numerous effective, safe and natural ways to fight obesity but why don't we being educated, informed or even alarmed that our body might gain unneeded extra weight? To avoid reaching such a condition, an individual needs to detect early causes to prevent overweight from happening, there are many causes that will lead to gain weight but there are two parameters that are strongly considered vital factors in weight gaining, these two are the amount of food intake and the physical activity. Our study will focus on the previously mentioned factors to help individuals to take immediate response to their current state.
{"title":"Towards Obesity Causes, Prevalence and Prevention","authors":"Ahmad Albu-Shamah, J. Zhan","doi":"10.1109/SocialCom.2013.128","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.128","url":null,"abstract":"Obesity is simply defined as the condition of being significantly overweight. It's the state where an individual weight is greater than and exceeding the healthy weight. Obesity and overweight has become the fastest growing epidemic affecting not only Americans but also the entire population in the world. Now, The question is how to fight Obesity? Surely there are numerous effective, safe and natural ways to fight obesity but why don't we being educated, informed or even alarmed that our body might gain unneeded extra weight? To avoid reaching such a condition, an individual needs to detect early causes to prevent overweight from happening, there are many causes that will lead to gain weight but there are two parameters that are strongly considered vital factors in weight gaining, these two are the amount of food intake and the physical activity. Our study will focus on the previously mentioned factors to help individuals to take immediate response to their current state.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115221977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-08DOI: 10.1109/SocialCom.2013.71
Yang Wang, Yun Huang, Claudia Louis
The practice of employing "the crowd" to help solve an organization's problems first became popular in the business sector, and has since spread to public and not-for-profit organizations. Input from the crowd can be solicited using different mechanisms involving various types of web-based applications, or the more recent trend of employing mobile phones with sensing capabilities. However, these crowd sourcing systems may lead to various privacy and security risks which can then hinder the adoption of these services. How to identify and address these potential risks in such systems has both research and practical value. This paper presents two aspects of our work in this emerging space. First, we describe a survey of potential privacy and security risks in mobile crowd sourcing systems (MCSS). Second, we describe our PEALS framework to support privacy-aware mobile crowd sourcing.
{"title":"Towards a Framework for Privacy-Aware Mobile Crowdsourcing","authors":"Yang Wang, Yun Huang, Claudia Louis","doi":"10.1109/SocialCom.2013.71","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.71","url":null,"abstract":"The practice of employing \"the crowd\" to help solve an organization's problems first became popular in the business sector, and has since spread to public and not-for-profit organizations. Input from the crowd can be solicited using different mechanisms involving various types of web-based applications, or the more recent trend of employing mobile phones with sensing capabilities. However, these crowd sourcing systems may lead to various privacy and security risks which can then hinder the adoption of these services. How to identify and address these potential risks in such systems has both research and practical value. This paper presents two aspects of our work in this emerging space. First, we describe a survey of potential privacy and security risks in mobile crowd sourcing systems (MCSS). Second, we describe our PEALS framework to support privacy-aware mobile crowd sourcing.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123731198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-08DOI: 10.1109/SocialCom.2013.105
S. Jajodia, W. Litwin, T. Schwarz
Encryption key loss problem is the Achilles's heel of cryptography. Key escrow helps, but favors disclosures. Schemes for recoverable encryption keys through noised secret sharing alleviate the dilemma. Key owner escrows a specifically encrypted backup. The recovery needs a large cloud. Cloud cost, money trail should rarefy illegal attempts. We now propose noised secret sharing schemes supporting discounts. The recovery request with discount code lowers the recovery complexity, easily by orders of magnitude. A smaller cloud may suffice for the same recovery timing. Alternatively, same cloud may provide faster recovery etc. Our schemes appear useful for users attracted to Big Data, but afraid of possibly humongous consequences of the key loss or data disclosure.
{"title":"Key Recovery Using Noised Secret Sharing with Discounts over Large Clouds","authors":"S. Jajodia, W. Litwin, T. Schwarz","doi":"10.1109/SocialCom.2013.105","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.105","url":null,"abstract":"Encryption key loss problem is the Achilles's heel of cryptography. Key escrow helps, but favors disclosures. Schemes for recoverable encryption keys through noised secret sharing alleviate the dilemma. Key owner escrows a specifically encrypted backup. The recovery needs a large cloud. Cloud cost, money trail should rarefy illegal attempts. We now propose noised secret sharing schemes supporting discounts. The recovery request with discount code lowers the recovery complexity, easily by orders of magnitude. A smaller cloud may suffice for the same recovery timing. Alternatively, same cloud may provide faster recovery etc. Our schemes appear useful for users attracted to Big Data, but afraid of possibly humongous consequences of the key loss or data disclosure.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121551290","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-08DOI: 10.1109/SOCIALCOM.2013.64
T. Yang, Radu E. Vlas, A. Yang, Cristina Vlas
An increasing number of companies and organizations have allowed employees (as well as business partners and contractors) to use their own devices to connect to company assets, resulting in the phenomena of BYOD (Bring Your Own Devices). Employees' own devices may pose greater threats against the corporation than its own assets would. They are perceived as more vulnerable and easier to become compromised than devices issued and controlled by the company. In this context, the need to manage the BYOD practice is undeniable. In this paper we propose the Risk Management Quintet as a model of understanding the BYOD practice. The relationships among the components of the Quintet, i.e., technology adoption, control, liabilities, user perception, and user behavior, are examined in the context of control mechanisms.
{"title":"Risk Management in the Era of BYOD: The Quintet of Technology Adoption, Controls, Liabilities, User Perception, and User Behavior","authors":"T. Yang, Radu E. Vlas, A. Yang, Cristina Vlas","doi":"10.1109/SOCIALCOM.2013.64","DOIUrl":"https://doi.org/10.1109/SOCIALCOM.2013.64","url":null,"abstract":"An increasing number of companies and organizations have allowed employees (as well as business partners and contractors) to use their own devices to connect to company assets, resulting in the phenomena of BYOD (Bring Your Own Devices). Employees' own devices may pose greater threats against the corporation than its own assets would. They are perceived as more vulnerable and easier to become compromised than devices issued and controlled by the company. In this context, the need to manage the BYOD practice is undeniable. In this paper we propose the Risk Management Quintet as a model of understanding the BYOD practice. The relationships among the components of the Quintet, i.e., technology adoption, control, liabilities, user perception, and user behavior, are examined in the context of control mechanisms.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121999679","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-08DOI: 10.1109/SocialCom.2013.125
Harun Pirim
Determining the number of clusters is required for most of the clustering algorithms. The number of clusters in a gene co-expression network is not known a prior. In this study, maximum independent set concept from graph theory is applied for a gene expression data set. The results indicate that employing independent set approach to approximate the number of clusters is promising.
{"title":"Finding Number of Clusters in a Gene Co-expression Network Using Independent Sets","authors":"Harun Pirim","doi":"10.1109/SocialCom.2013.125","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.125","url":null,"abstract":"Determining the number of clusters is required for most of the clustering algorithms. The number of clusters in a gene co-expression network is not known a prior. In this study, maximum independent set concept from graph theory is applied for a gene expression data set. The results indicate that employing independent set approach to approximate the number of clusters is promising.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126332913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-08DOI: 10.1109/SOCIALCOM.2013.102
S. S. Rodríguez, Ana Fernández Vilas, R. Redondo, J. Pazos-Arias
This paper addresses the problem of mining users' interest from the vast, noise, unstructured and dynamic data generated on social media sites, taking Twitter as case study. The mining process uses different Natural Language Processing techniques to extract the relevant words from subscribers' tweets and applies cluster analysis over them. We evaluate the performance of three different tag clustering algorithms -PAM, Affinity Propagation and UPGMA- when considering the hyperlink structure of Wikipedia as external source for semantic closeness among words. We provide a solution which can be developed without any a-priori knowledge about the number and category of topics, neither a priori knowledge about the users we are applying the extraction for. This solution is based on using an unsupervised measure of the clustering quality (Silhouette width) to estimate the parameters of the cluster analysis. Finally, as human feedback is not as reliable as expected, we validate the approach by using Twitter hash tags - the implicit classifying method used by Twitter users to organise their tweets.
{"title":"Comparing Tag Clustering Algorithms for Mining Twitter Users' Interests","authors":"S. S. Rodríguez, Ana Fernández Vilas, R. Redondo, J. Pazos-Arias","doi":"10.1109/SOCIALCOM.2013.102","DOIUrl":"https://doi.org/10.1109/SOCIALCOM.2013.102","url":null,"abstract":"This paper addresses the problem of mining users' interest from the vast, noise, unstructured and dynamic data generated on social media sites, taking Twitter as case study. The mining process uses different Natural Language Processing techniques to extract the relevant words from subscribers' tweets and applies cluster analysis over them. We evaluate the performance of three different tag clustering algorithms -PAM, Affinity Propagation and UPGMA- when considering the hyperlink structure of Wikipedia as external source for semantic closeness among words. We provide a solution which can be developed without any a-priori knowledge about the number and category of topics, neither a priori knowledge about the users we are applying the extraction for. This solution is based on using an unsupervised measure of the clustering quality (Silhouette width) to estimate the parameters of the cluster analysis. Finally, as human feedback is not as reliable as expected, we validate the approach by using Twitter hash tags - the implicit classifying method used by Twitter users to organise their tweets.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124715786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-08DOI: 10.1109/SocialCom.2013.23
K. Bijon, R. Krishnan, R. Sandhu
Recently, attribute based access control (ABAC) has received considerable attention from the security community for its policy flexibility and dynamic decision making capabilities. In ABAC, authorization decisions are based on various attributes of entities involved in the access (e.g., users, subjects, objects, context, etc.). In an ABAC system, correct attribute assignment to different entities is necessary for ensuring appropriate access. Although considerable research has been conducted on ABAC, so far constraints specification on attribute assignment to entities has not been systematically studied in the literature. In this paper, we propose an attribute-based constraints specification language(ABCL) for expressing a variety of constraints on values that different attributes of various entities in the system can take. ABCL can be used to specify constraints on a single attribute or across multiple attributes of a particular entity. Furthermore, constraints on attributes assignment across multiple entities (e.g., attributes of different users) can also be specified. Finally, we demonstrate the usefulness of ABCL in practical usage scenarios including banking domains.
{"title":"Towards an Attribute Based Constraints Specification Language","authors":"K. Bijon, R. Krishnan, R. Sandhu","doi":"10.1109/SocialCom.2013.23","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.23","url":null,"abstract":"Recently, attribute based access control (ABAC) has received considerable attention from the security community for its policy flexibility and dynamic decision making capabilities. In ABAC, authorization decisions are based on various attributes of entities involved in the access (e.g., users, subjects, objects, context, etc.). In an ABAC system, correct attribute assignment to different entities is necessary for ensuring appropriate access. Although considerable research has been conducted on ABAC, so far constraints specification on attribute assignment to entities has not been systematically studied in the literature. In this paper, we propose an attribute-based constraints specification language(ABCL) for expressing a variety of constraints on values that different attributes of various entities in the system can take. ABCL can be used to specify constraints on a single attribute or across multiple attributes of a particular entity. Furthermore, constraints on attributes assignment across multiple entities (e.g., attributes of different users) can also be specified. Finally, we demonstrate the usefulness of ABCL in practical usage scenarios including banking domains.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115021730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2013-09-08DOI: 10.1109/SocialCom.2013.158
Abdulaziz Almehmadi, Michael Bourque, K. El-Khatib
While millions of individuals around the globe use social media every second to disseminate, in some form, their emotions and experiences, there are still some situational challenges these individuals face while trying to share experience over social media. This work introduces the idea of using a Brain Computer Interface device to detect human emotion, which is then paired with geo-location information and automatically posted to a popular social media service. A complete architecture of a system that implements this idea is proposed and implemented, where Brain Pattern Analysis is performed using an Electroencephalogram device and a mobile computing device.
{"title":"A Tweet of the Mind: Automated Emotion Detection for Social Media Using Brain Wave Pattern Analysis","authors":"Abdulaziz Almehmadi, Michael Bourque, K. El-Khatib","doi":"10.1109/SocialCom.2013.158","DOIUrl":"https://doi.org/10.1109/SocialCom.2013.158","url":null,"abstract":"While millions of individuals around the globe use social media every second to disseminate, in some form, their emotions and experiences, there are still some situational challenges these individuals face while trying to share experience over social media. This work introduces the idea of using a Brain Computer Interface device to detect human emotion, which is then paired with geo-location information and automatically posted to a popular social media service. A complete architecture of a system that implements this idea is proposed and implemented, where Brain Pattern Analysis is performed using an Electroencephalogram device and a mobile computing device.","PeriodicalId":129308,"journal":{"name":"2013 International Conference on Social Computing","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116439038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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