Uncovering Deception in Social Media
A Special Issue in Springer Journal Social Network Analysis and Mining
Guest Editors: Huan Liu (ASU), Jiawei Han (UIUC), and Hiroshi Motoda
(Osaka University)
Twitter, and LinkedIn are some examples of an inordinate number of social
media services that are loved and used by people of all walks of life for
various purposes such as sharing news, expressing opinions, documenting
thoughts, launching political campaigns, maintaining and developing
friendships or professional connection. Some key characteristics of social
media include low entry barrier, instant updates (thus, instant
gratification), large numbers of friends, open platform, and anonymity.
The last two properties make people comfortable to become users but also
make social media vulnerable to activities of ill intentions.
Deception in social media is an epitome of such activities. Deception is a
distortion with an intention to mislead users, analysts, organizations,
etc. A distortion can be about content, source, identity, age, sex, or
location, among many. Deception is encouraged or made easy by the unique
circumstances of social media. Deception is rampant in social media for a
wide range of reasons, being an innocent white lie or resulting in a dire
consequence where one?s job or life is at stake. Hence, it is important to
research deception in social media. It is necessary to uncover deception
in social media so that we can improve our awareness and confidence in
using social media, design and develop countermeasures to ?separate wheat
from chaff? to minimize negative impact of deception.
This special issue aims to identify issues of deception in social media,
review the state-of-the-art research on deception, offer a convenient
venue for sharing multi-disciplinary research findings, and identifying
pressing issues and future challenges.
Topics of interest include, but are not limited to, the following
* Forms of deceptions: disinformation, misinformation, honeypot accounts,
wiki-circularity, and impersonation
* Features associated with deceptions: linguistic features, interactive
features, etc.
* Sources of deceptions: adversaries, hoax, privacy related, white lies,
sites of special interests/design
* Handling deceptions: assessment, detection, prediction, and tracking
* Deception theories and practices: how extant social and psychological
theories can be adapted to social media study, new needs of social media
* Data for deception research: benchmarks, and data of good practice
* Performance evaluation: evolving nature of deception, ground truth, and
metrics
* Applications: Health, Cybersecurity, Online Search, Online
Advertisement, Online Communications,
* Related topics: provenance, trust, credibility, spam, gaming, and fraud
For submission, please visit http://www.editorialmanager.com/snam/ by
selecting Article Type "S.I.: Uncovering Deception in Social Media"
Important Dates: Submissions due on June 15, 2013; Review results due on
September 15, 2013; Manuscripts due on November 15, 2013; Expected
publication date ? early 2014.
