Abstract: The massive development of online social networks
allows users to post and share their opinions on various topics.
With this huge volume of opinion, it is interesting to extract and
interpret these information for different domains, e.g., product and
service benchmarking, politic, system of recommendation. This is
why opinion detection is one of the most important research tasks.
It consists on differentiating between opinion data and factual data.
The difficulty of this task is to determine an approach which returns
opinionated document. Generally, there are two approaches used
for opinion detection i.e. Lexical based approaches and Machine
Learning based approaches. In Lexical based approaches, a dictionary
of sentimental words is used, words are associated with weights. The
opinion score of document is derived by the occurrence of words from
this dictionary. In Machine learning approaches, usually a classifier
is trained using a set of annotated document containing sentiment,
and features such as n-grams of words, part-of-speech tags, and
logical forms. Majority of these works are based on documents text
to determine opinion score but dont take into account if these texts
are really correct. Thus, it is interesting to exploit other information
to improve opinion detection. In our work, we will develop a new
way to consider the opinion score. We introduce the notion of
trust score. We determine opinionated documents but also if these
opinions are really trustable information in relation with topics. For
that we use lexical SentiWordNet to calculate opinion and trust
scores, we compute different features about users like (numbers of
their comments, numbers of their useful comments, Average useful
review). After that, we combine opinion score and trust score to
obtain a final score. We applied our method to detect trust opinions in
TRIPADVISOR collection. Our experimental results report that the
combination between opinion score and trust score improves opinion
detection.
Abstract: Location sharing is a fundamental service in mobile Online Social Networks (mOSNs), which raises significant privacy concerns in recent years. Now, most location-based service applications adopt client/server architecture. In this paper, a location sharing system, named CSLocShare, is presented to provide flexible privacy-preserving location sharing with client/server architecture in mOSNs. CSLocShare enables location sharing between both trusted social friends and untrusted strangers without the third-party server. In CSLocShare, Location-Storing Social Network Server (LSSNS) provides location-based services but do not know the users’ real locations. The thorough analysis indicates that the users’ location privacy is protected. Meanwhile, the storage and the communication cost are saved. CSLocShare is more suitable and effective in reality.
Abstract: Community detection is an extremely useful technique
in understanding the structure and function of a social network.
Louvain algorithm, which is based on Newman-Girman modularity
optimization technique, is extensively used as a computationally
efficient method extract the communities in social networks. It
has been suggested that the nodes that are in close geographical
proximity have a higher tendency of forming communities. Variants
of the Newman-Girman modularity measure such as dist-modularity
try to normalize the effect of geographical proximity to extract
geographically dispersed communities, at the expense of losing
the information about the geographically proximate communities.
In this work, we propose a method to extract geographically
dispersed communities while preserving the information about the
geographically proximate communities, by analyzing the ‘community
network’, where the centroids of communities would be considered as
network nodes. We suggest that the inter-community link strengths,
which are normalized over the community sizes, may be used
to identify and extract the ‘overlay communities’. The overlay
communities would have relatively higher link strengths, despite
being relatively apart in their spatial distribution. We apply this
method to the Gowalla online social network, which contains
the geographical signatures of its users, and identify the overlay
communities within it.
Abstract: Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.
Abstract: Urbanization, population growth, climate change and the current increase in water demand have made the adoption of innovative demand management strategies crucial to the water industry. Water conservation in urban areas has to be improved by encouraging consumers to adopt more sustainable habits and behaviours. This includes informing and educating them about their households’ water consumption and advising them about ways to achieve significant savings on a daily basis. This paper presents a study conducted in the context of the European FP7 WISDOM Project. By integrating innovative Information and Communication Technologies (ICT) frameworks, this project aims at achieving a change in water savings. More specifically, behavioural change will be attempted by implementing smart meters and in-home displays in a trial group of selected households within Cardiff (UK). Using this device, consumers will be able to receive feedback and information about their consumption but will also have the opportunity to compare their consumption to the consumption of other consumers and similar households. Following an initial survey, it appeared necessary to implement these in-home displays in a way that matches consumer's motivations to save water. The results demonstrated the importance of various factors influencing people’s daily water consumption. Both the relevant literature on the subject and the results of our survey therefore led us to include within the in-home device a variety of elements. It first appeared crucial to make consumers aware of the economic aspect of water conservation and especially of the significant financial savings that can be achieved by reducing their household’s water consumption on the long term. Likewise, reminding participants of the impact of their consumption on the environment by making them more aware of water scarcity issues around the world will help increasing their motivation to save water. Additionally, peer pressure and social comparisons with neighbours and other consumers, accentuated by the use of online social networks such as Facebook or Twitter, will likely encourage consumers to reduce their consumption. Participants will also be able to compare their current consumption to their past consumption and to observe the consequences of their efforts to save water through diverse graphs and charts. Finally, including a virtual water game within the display will help the whole household, children and adults, to achieve significant reductions by providing them with simple tips and advice to save water on a daily basis. Moreover, by setting daily and weekly goals for them to reach, the game will expectantly generate cooperation between family members. Members of each household will indeed be encouraged to work together to reduce their water consumption within different rooms of the house, such as the bathroom, the kitchen, or the toilets. Overall, this study will allow us to understand the elements that attract consumers the most and the features that are most commonly used by the participants. In this way, we intend to determine the main factors influencing water consumption in order to identify the measures that will most encourage water conservation in both the long and short term.
Abstract: This study found that most corporate personnel are
using social media to communicate with colleagues to make the
process of working more efficient. Complete satisfaction occurred on
the use of security within the University’s computer network. The
social network usage for communication, collaboration,
entertainment and demonstrating concerns accounted for fifty percent
of variance to predict interpersonal relationships of corporate
personnel. This evaluation on the effectiveness of social networking
involved 213 corporate personnel’s. The data was collected by
questionnaires. This data was analyzed by using percentage, mean,
and standard deviation.
The results from the analysis and the effectiveness of using online
social networks were derived from the attitude of private users and
safety data within the security system. The results showed that the
effectiveness on the use of an online social network for corporate
personnel of Suan Sunandha Rajabhat University was specifically at
a good level, and the overall effects of each aspect was (Ẋ=3.11).
Abstract: In this paper we are presenting some spamming
techniques their behaviour and possible solutions. We have analyzed
how Spammers enters into online social networking sites (OSNSs) to
target them and diverse techniques used by them for this purpose.
Spamming is very common issue in present era of Internet
especially through Online Social Networking Sites (like Facebook,
Twitter, and Google+ etc.). Spam messages keep wasting Internet
bandwidth and the storage space of servers. On social networking
sites; spammers often disguise themselves by creating fake accounts
and hijacking user’s accounts for personal gains. They behave like
normal user and they continue to change their spamming strategy.
Following spamming techniques are discussed in this paper like
clickjacking, social engineered attacks, cross site scripting, URL
shortening, and drive by download. We have used elgg framework
for demonstration of some of spamming threats and respective
implementation of solutions.
Abstract: As a matter of the fact that online social networks like
Twitter, Facebook and MySpace have experienced an extensive
growth in recent years. Social media offers individuals with a tool for
communicating and interacting with one another. These social
networks enable people to stay in touch with other people and
express themselves. This process makes the users of online social
networks active creators of content rather than being only consumers
of traditional media. That’s why millions of people show strong
desire to learn the methods and tools of digital content production
and necessary communication skills. However, the booming interest
in communication and interaction through online social networks and
high level of eagerness to invent and implement the ways to
participate in content production raise some privacy and security
concerns.
This presentation aims to open the assumed revolutionary,
democratic and liberating nature of the online social media up for
discussion by reviewing some recent political developments in
Turkey. Firstly, the role of Internet and online social networks in
mobilizing collective movements through social interactions and
communications will be questioned. Secondly, some cases from Gezi
and Okmeydanı Protests and also December 17-25 period will be
presented in order to illustrate misinformation and manipulation in
social media and violation of individual privacy through online social
networks in order to damage social unity and stability contradictory
to democratic nature of online social networking.
Abstract: There is a real threat on the VIPs personal pages on
the Social Network Sites (SNS). The real threats to these pages is
violation of privacy and theft of identity through creating fake pages
that exploit their names and pictures to attract the victims and spread
of lies. In this paper, we propose a new secure architecture that
improves the trusting and finds an effective solution to reduce fake
pages and possibility of recognizing VIP pages on SNS. The
proposed architecture works as a third party that is added to
Facebook to provide the trust service to personal pages for VIPs.
Through this mechanism, it works to ensure the real identity of the
applicant through the electronic authentication of personal
information by storing this information within content of their
website. As a result, the significance of the proposed architecture is
that it secures and provides trust to the VIPs personal pages.
Furthermore, it can help to discover fake page, protect the privacy,
reduce crimes of personality-theft, and increase the sense of trust and
satisfaction by friends and admirers in interacting with SNS.