Social Networks Research Aspects: A Vast and Fast Survey Focused on the Issue of Privacy in Social Network Sites <s> 4) Crawling: <s> Given a huge online social network, how do we retrieve information from it through crawling? Even better, how do we improve the crawling performance by using parallel crawlers that work independently? In this paper, we present the framework of parallel crawlers for online social networks, utilizing a centralized queue. To show how this works in practice, we describe our implementation of the crawlers for an online auction website. The crawlers work independently, therefore the failing of one crawler does not affect the others at all. The framework ensures that no redundant crawling would occur. Using the crawlers that we built, we visited a total of approximately 11 million auction users, about 66,000 of which were completely crawled. <s> BIB001 </s> Social Networks Research Aspects: A Vast and Fast Survey Focused on the Issue of Privacy in Social Network Sites <s> 4) Crawling: <s> Social networking sites have been increasingly gaining popularity. Well-known sites such as Facebook have been reporting growth rates as high as 3% per week. Many social networking sites have millions of registered users who use these sites to share photographs, contact long-lost friends, establish new business contacts and to keep in touch. In this paper, we investigate how easy it would be for a potential attacker to launch automated crawling and identity theft attacks against a number of popular social networking sites in order to gain access to a large volume of personal user information. The first attack we present is the automated identity theft of existing user profiles and sending of friend requests to the contacts of the cloned victim. The hope, from the attacker's point of view, is that the contacted users simply trust and accept the friend request. By establishing a friendship relationship with the contacts of a victim, the attacker is able to access the sensitive personal information provided by them. In the second, more advanced attack we present, we show that it is effective and feasible to launch an automated, cross-site profile cloning attack. In this attack, we are able to automatically create a forged profile in a network where the victim is not registered yet and contact the victim's friends who are registered on both networks. Our experimental results with real users show that the automated attacks we present are effective and feasible in practice. <s> BIB002 </s> Social Networks Research Aspects: A Vast and Fast Survey Focused on the Issue of Privacy in Social Network Sites <s> 4) Crawling: <s> Web crawlers are highly automated and seldom regulated manually. The diversity of crawler activities often leads to ethical problems such as spam and service attacks. In this research, quantitative models are proposed to measure the web crawler ethics based on their behaviors on web servers. We investigate and define rules to measure crawler ethics, referring to the extent to which web crawlers respect the regulations set forth in robots.txt configuration files. We propose a vector space model to represent crawler behavior and measure the ethics of web crawlers based on the behavior vectors. The results show that ethicality scores vary significantly among crawlers. Most commercial web crawlers' behaviors are ethical. However, many commercial crawlers still consistently violate or misinterpret certain robots.txt rules. We also measure the ethics of big search engine crawlers in terms of return on investment. The results show that Google has a higher score than other search engines for a US website but has a lower score than Baidu for Chinese websites. <s> BIB003
To analyze the information of SNSs first we must acquire it. One of the most important ways to do this is using crawlers. Crawlers generally should have some specifications like being up to date and having mechanisms to prevent fetching the same page more than once. According to special characteristics of social networks like the huge size, and the auto crawling prevention mechanisms that SNSs use it seems that we need special kind of crawlers. In BIB001 noting the large size of data, and the different way of data presentation in social networks a parallel crawler is proposed for crawling social networks. In BIB002  facebook is crawled and the problem of facing with CAPTCHAs is noted. In BIB003 the ethicality of web crawlers is discussed.