Online deception in social media

Abstract

A S E D technologies has revolutionized the way content is generated and exchanged through the Internet, leading to proliferation of social-media applications and services. Social media enable creation and exchange of user-generated content and design of a range of Internet-based applications. This growth is fueled not only by more services but also by the rate of their adoption by users. From 2005 to 2013, users and developers alike saw a 64% increase in the number of people using social media; 1 for instance, Twitter use increased 10% from 2010 to 2013, and 1.2 billion users connected in 2013 through Facebook and Twitter accounts. 24 However, the ease of getting an account also makes it easy for individuals to deceive one another. Previous work on deception found that people in general lie routinely, and several efforts have sought to detect and understand deception. 20 Deception has been used in various contexts throughout human history (such as in World War II and the Trojan War) to In social media, deception can involve content, sender, and communication channel or all three together.The nature of a social medium can influence the likelihood of deception and its success for each deception technique.Deception detection and prevention are complicated by lack of standard online deception detection, of a computationally efficient method for detecting deception in large online communities, and of social media developers looking to prevent deception.

Research of Deceptive Review Detection Based on Target Product Identification and Metapath Feature Weight Calculation

“…Given a product and a rating level , ∈ [1,5], we gather the reviewers set , of the product rating for . For ∀ ∈ , , the proportion , of the reviews with rating is defined as the product rating scale, as shown in (2).…”

“…If a product has a lot of praise, the user will show a greater tendency to purchase. Deceptive detection and prevention are complicated by lack of standard online deception detection, a computationally efficient method for detecting deception in large online communities, and social media developers looking to prevent deception [1]. The deceptive reviews are fake reviews deliberately posted by a few illegal users.…”

The projection and measurement of cyberpower

“…Within cyberspace though, attribution may not be straightforward and misinformation is rife. Social media in particular has been noted as providing an environment in which individuals have been deceived, sometimes with devastating personal consequences (Tsikerdekis and Zeadally, 2014). Established media organisations and democratic governments with an online presence strive to ensure the credibility of all information that they broadcast and that it is not perceived as state-sponsored propaganda.…”

Fraud Detection through Modified K Means Clustring in Social Media

“…The privacy of the users will be at stake if deception takes place. [1,4,5] the deception will cause falsifying information to be transmitted from source to the destination. Deception can be at the smaller scale or at the large level.…”

“…Deception which takes place over the internet is under the category of Online Deception. [6,7]When falsifying information is provided by the users then the other users which are affected by the deception are potential victims. General technology behind the deception will be online social media.…”