Social network contains the interaction between social members, which constitutes the structure and attribute of social network. The interactive relationship of social network contains a lot of personal privacy inform...Social network contains the interaction between social members, which constitutes the structure and attribute of social network. The interactive relationship of social network contains a lot of personal privacy information. The direct release of social network data will cause the disclosure of privacy information. Aiming at the dynamic characteristics of social network data release, a new dynamic social network data publishing method based on differential privacy was proposed. This method was consistent with differential privacy. It is named DDPA (Dynamic Differential Privacy Algorithm). DDPA algorithm is an improvement of privacy protection algorithm in static social network data publishing. DDPA adds noise which follows Laplace to network edge weights. DDPA identifies the edge weight information that changes as the number of iterations increases, adding the privacy protection budget. Through experiments on real data sets, the results show that the DDPA algorithm satisfies the user’s privacy requirement in social network. DDPA reduces the execution time brought by iterations and reduces the information loss rate of graph structure.展开更多
With the increasing prevalence of social networks, more and more social network data are published for many applications, such as social network analysis and data mining. However, this brings privacy problems. For exa...With the increasing prevalence of social networks, more and more social network data are published for many applications, such as social network analysis and data mining. However, this brings privacy problems. For example, adversaries can get sensitive information of some individuals easily with little background knowledge. How to publish social network data for analysis purpose while preserving the privacy of individuals has raised many concerns. Many algorithms have been proposed to address this issue. In this paper, we discuss this privacy problem from two aspects： attack models and countermeasures. We analyse privacy conceres, model the background knowledge that adversary may utilize and review the recently developed attack models. We then survey the state-of-the-art privacy preserving methods in two categories： anonymization methods and differential privacy methods. We also provide research directions in this area.展开更多
Using social networking services is becoming more popular day by day. The websites of the social networks like face-book currently are among the most popular internet services just after giant portals such as Yahoo, M...Using social networking services is becoming more popular day by day. The websites of the social networks like face-book currently are among the most popular internet services just after giant portals such as Yahoo, MSN and search engines like Google. One of the main problems in analyzing these networks is the prediction of relationships between people in the network. The purpose of this paper is to forecast the friendship of a person with a new person using existing data on Flickr website accurately. In this paper, we achieved about 90% percent correct prediction with regards to the results which are obtained by using data mining methods.展开更多
This research is about the nuisances of social media applications on a Wi-Fi network at a university campus in Ghana. The aim was to access the security risk on the network, the speed of the network, and the data cons...This research is about the nuisances of social media applications on a Wi-Fi network at a university campus in Ghana. The aim was to access the security risk on the network, the speed of the network, and the data consumption of those platforms on the network. Network Mapper (Nmap Zenmap) Graphical User Interface 7.80 application was used to scan the various social media platforms to identify the protocols, ports, services, etc. to enable in accessing the vulnerability of the network. Data consumption of users’ mobile devices was collected and analyzed. Device Accounting (DA) based on the various social media applications was used. The results of the analysis revealed that the network is prone to attacks due to the nature of the protocols, ports, and services on social media applications. The numerous users with average monthly data consumption per user of 4 gigabytes, 300 megabytes on social media alone are a clear indication of high traffic as well as the cost of maintaining the network. A URL filtering of the social media websites was proposed on Rockus Outdoor AP to help curb the nuisance.展开更多
In 2008, the Brazilian Department of Science and Technology created the INCTs (Brazilian Science and Technology Institutes). One of them was the Cancer Control INCT. Due to its importance and considering that there ar...In 2008, the Brazilian Department of Science and Technology created the INCTs (Brazilian Science and Technology Institutes). One of them was the Cancer Control INCT. Due to its importance and considering that there are different groups working together in the same area, it is important that they collaborate intensely. Envisioning an empowerment of scientific collaboration, the BRINCA project was created to support a set of analyses of the social networks from this particular INCT. These analyses were created by mining curricular and publications bases, and identifying different types of scientific relationships and areas. We were able to observe, for instance, how the interaction is amongst researchers from related areas, which researchers were more collaborative and which ones were isolated from the network. These analyzes were used by the INCT coordination to understand and act to improve scientific collaboration.展开更多
Social media plays a crucial role in the organization of massive social movements. However, the sheer quantity of data generated by the events as well as the data collection restrictions that researchers encounter, le...Social media plays a crucial role in the organization of massive social movements. However, the sheer quantity of data generated by the events as well as the data collection restrictions that researchers encounter, leads to a series of challenges for researchers who want to analyze dynamic public discourse and opinion in response to and in the creation of world events. In this paper we present gatherTweet, a Python package that helps researchers efficiently collect social media data for events that are composed of many decentralized actions (across both space and time). The package is useful for studies that require analysis of the organizational or baseline messaging before an action, the action itself, and the effects of the action on subsequent public discourse. By capturing these aspects of world events gatherTweet enables the study of events and actions like protests, natural disasters, and elections.展开更多
The rising popularity of online social networks (OSNs), such as Twitter, Facebook, MySpace, and LinkedIn, in recent years has sparked great interest in sentiment analysis on their data. While many methods exist for id...The rising popularity of online social networks (OSNs), such as Twitter, Facebook, MySpace, and LinkedIn, in recent years has sparked great interest in sentiment analysis on their data. While many methods exist for identifying sentiment in OSNs such as communication pattern mining and classification based on emoticon and parts of speech, the majority of them utilize a suboptimal batch mode learning approach when analyzing a large amount of real time data. As an alternative we present a stream algorithm using Modified Balanced Winnow for sentiment analysis on OSNs. Tested on three real-world network datasets, the performance of our sentiment predictions is close to that of batch learning with the ability to detect important features dynamically for sentiment analysis in data streams. These top features reveal key words important to the analysis of sentiment.展开更多
The evolution of social media in the recent years promoted the appearance of a new category: social media based on check-in. It enables the user to define their identity through information sharing. This paper aims to...The evolution of social media in the recent years promoted the appearance of a new category: social media based on check-in. It enables the user to define their identity through information sharing. This paper aims to show the evolution of these media highlighting the effects and changes they cause in society through Super Bowl XLVI scenario, besides indicating the important role they have for the companies and marketing.展开更多
After reviewing the development of industrial manufacturing, a novel concept called social manufacturing(SM) and service are proposed as an innovative manufacturing solution for the coming personalized customization e...After reviewing the development of industrial manufacturing, a novel concept called social manufacturing(SM) and service are proposed as an innovative manufacturing solution for the coming personalized customization era. SM can realize a customer's requirements of "from mind to products", and fulfill tangible and intangible needs of a prosumer, i.e., producer and consumer at the same time. It represents a manufacturing trend,and is expected to become popular in more and more industries.First, a comparison between mass customization and SM is given out, and the basis and motivation from social network to SM is analyzed. Then, its basic theories and supporting technologies,like Internet of Things(Io T), social networks, cloud computing,3 D printing, and intelligent systems, are introduced and analyzed,and an SM platform prototype is developed. Finally, three transformation modes towards SM and 3 D printing are suggested for different user cases.展开更多
文摘Social network contains the interaction between social members, which constitutes the structure and attribute of social network. The interactive relationship of social network contains a lot of personal privacy information. The direct release of social network data will cause the disclosure of privacy information. Aiming at the dynamic characteristics of social network data release, a new dynamic social network data publishing method based on differential privacy was proposed. This method was consistent with differential privacy. It is named DDPA (Dynamic Differential Privacy Algorithm). DDPA algorithm is an improvement of privacy protection algorithm in static social network data publishing. DDPA adds noise which follows Laplace to network edge weights. DDPA identifies the edge weight information that changes as the number of iterations increases, adding the privacy protection budget. Through experiments on real data sets, the results show that the DDPA algorithm satisfies the user’s privacy requirement in social network. DDPA reduces the execution time brought by iterations and reduces the information loss rate of graph structure.
文摘With the increasing prevalence of social networks, more and more social network data are published for many applications, such as social network analysis and data mining. However, this brings privacy problems. For example, adversaries can get sensitive information of some individuals easily with little background knowledge. How to publish social network data for analysis purpose while preserving the privacy of individuals has raised many concerns. Many algorithms have been proposed to address this issue. In this paper, we discuss this privacy problem from two aspects： attack models and countermeasures. We analyse privacy conceres, model the background knowledge that adversary may utilize and review the recently developed attack models. We then survey the state-of-the-art privacy preserving methods in two categories： anonymization methods and differential privacy methods. We also provide research directions in this area.
文摘Using social networking services is becoming more popular day by day. The websites of the social networks like face-book currently are among the most popular internet services just after giant portals such as Yahoo, MSN and search engines like Google. One of the main problems in analyzing these networks is the prediction of relationships between people in the network. The purpose of this paper is to forecast the friendship of a person with a new person using existing data on Flickr website accurately. In this paper, we achieved about 90% percent correct prediction with regards to the results which are obtained by using data mining methods.
文摘This research is about the nuisances of social media applications on a Wi-Fi network at a university campus in Ghana. The aim was to access the security risk on the network, the speed of the network, and the data consumption of those platforms on the network. Network Mapper (Nmap Zenmap) Graphical User Interface 7.80 application was used to scan the various social media platforms to identify the protocols, ports, services, etc. to enable in accessing the vulnerability of the network. Data consumption of users’ mobile devices was collected and analyzed. Device Accounting (DA) based on the various social media applications was used. The results of the analysis revealed that the network is prone to attacks due to the nature of the protocols, ports, and services on social media applications. The numerous users with average monthly data consumption per user of 4 gigabytes, 300 megabytes on social media alone are a clear indication of high traffic as well as the cost of maintaining the network. A URL filtering of the social media websites was proposed on Rockus Outdoor AP to help curb the nuisance.
文摘In 2008, the Brazilian Department of Science and Technology created the INCTs (Brazilian Science and Technology Institutes). One of them was the Cancer Control INCT. Due to its importance and considering that there are different groups working together in the same area, it is important that they collaborate intensely. Envisioning an empowerment of scientific collaboration, the BRINCA project was created to support a set of analyses of the social networks from this particular INCT. These analyses were created by mining curricular and publications bases, and identifying different types of scientific relationships and areas. We were able to observe, for instance, how the interaction is amongst researchers from related areas, which researchers were more collaborative and which ones were isolated from the network. These analyzes were used by the INCT coordination to understand and act to improve scientific collaboration.
文摘Social media plays a crucial role in the organization of massive social movements. However, the sheer quantity of data generated by the events as well as the data collection restrictions that researchers encounter, leads to a series of challenges for researchers who want to analyze dynamic public discourse and opinion in response to and in the creation of world events. In this paper we present gatherTweet, a Python package that helps researchers efficiently collect social media data for events that are composed of many decentralized actions (across both space and time). The package is useful for studies that require analysis of the organizational or baseline messaging before an action, the action itself, and the effects of the action on subsequent public discourse. By capturing these aspects of world events gatherTweet enables the study of events and actions like protests, natural disasters, and elections.
文摘The rising popularity of online social networks (OSNs), such as Twitter, Facebook, MySpace, and LinkedIn, in recent years has sparked great interest in sentiment analysis on their data. While many methods exist for identifying sentiment in OSNs such as communication pattern mining and classification based on emoticon and parts of speech, the majority of them utilize a suboptimal batch mode learning approach when analyzing a large amount of real time data. As an alternative we present a stream algorithm using Modified Balanced Winnow for sentiment analysis on OSNs. Tested on three real-world network datasets, the performance of our sentiment predictions is close to that of batch learning with the ability to detect important features dynamically for sentiment analysis in data streams. These top features reveal key words important to the analysis of sentiment.
文摘The evolution of social media in the recent years promoted the appearance of a new category: social media based on check-in. It enables the user to define their identity through information sharing. This paper aims to show the evolution of these media highlighting the effects and changes they cause in society through Super Bowl XLVI scenario, besides indicating the important role they have for the companies and marketing.
基金supported in part by the National Natural Science Foundation of China(61233001,61773381,71232006,61304201,61533019,61773382)Finnish TEKES’s project“So Ma2020:Social Manufacturing”(2015-2017,211560)Chinese Guangdong’s S&T project(2015B010103001,2016B090910001)
文摘After reviewing the development of industrial manufacturing, a novel concept called social manufacturing(SM) and service are proposed as an innovative manufacturing solution for the coming personalized customization era. SM can realize a customer's requirements of "from mind to products", and fulfill tangible and intangible needs of a prosumer, i.e., producer and consumer at the same time. It represents a manufacturing trend,and is expected to become popular in more and more industries.First, a comparison between mass customization and SM is given out, and the basis and motivation from social network to SM is analyzed. Then, its basic theories and supporting technologies,like Internet of Things(Io T), social networks, cloud computing,3 D printing, and intelligent systems, are introduced and analyzed,and an SM platform prototype is developed. Finally, three transformation modes towards SM and 3 D printing are suggested for different user cases.
