POLMETH Archives

Political Methodology Society

POLMETH@LISTSERV.WUSTL.EDU

Options: Use Forum View

Use Monospaced Font
Show Text Part by Default
Show All Mail Headers

Message: [<< First] [< Prev] [Next >] [Last >>]
Topic: [<< First] [< Prev] [Next >] [Last >>]
Author: [<< First] [< Prev] [Next >] [Last >>]

Print Reply
Subject:
From:
Andrea Passarella <[log in to unmask]>
Reply To:
Political Methodology Society <[log in to unmask]>, Andrea Passarella <[log in to unmask]>
Date:
Mon, 22 Apr 2024 15:30:02 +0000
Content-Type:
text/plain
Parts/Attachments:
text/plain (63 lines)
------------------------------------------------------------------------------
CALL FOR PAPERS

Elsevier Online Social Networks and Media Journal (OSNEM)

Special issue on
AI in Online Social Networks: opportunities and challenges

Submission Deadline: Continuous submissions until July 31st, 2024
https://www.sciencedirect.com/journal/online-social-networks-and-media
------------------------------------------------------------------------------
 
Online Social Networks and Media are a fundamental component of everyday life and the use of AI technologies in OSNEM can further boost their role. The use of AI in online social networks offers great opportunities and, at the same time, raises several challenges. AI's ability to analyze vast amounts of data in real-time allows social media platforms to offer highly personalized experiences to users. The use of AI may raise concerns about ethical issues such as privacy, algorithmic bias, misinformation, etc., but AI can also be used for content moderation on social media to detect and remove harmful or inappropriate content, identifying and mitigating the spread of fake news. etc. The use of AI on OSNEM can promote the democratic processes by facilitating the dissemination of information and encourage political engagement. On the other hand, AI algorithms can create echo chambers, influence voting behavior and generate significant risks for democracy. AI-driven security measures can help to protect OSNEM users from fraud and privacy breaches but, malicious actors can also use AI to support their attacks. The exponential diffusion of generative AI adds novel dimensions to this landscape, on the one hand supporting novel forms of interactions spanning into the Metaverse, but on the other hand exposing vulnerable users to dramatic threats.

The aim of this special issue is to push the state of the art in using AI in OSNEM, by presenting quantitative contributions that investigate the opportunities and challenges of using AI in Online Social Networks.  Within this framework, topics include, but are not limited to:

- Using AI in OSNEM for personalization, efficiency, and recommendations;
- AI-based studies for analysis and modelling of information and opinion dynamics in OSNEM;
- AI-based predictions based on OSNEM data analysis;
- AI impact on OSNEM security, trustworthiness and privacy;
- Generative AI  in OSNEM;
- AI and social networking in the Metaverse;
- AI methodologies for large-scale OSNEM data collection and analysis
- AI methods to safeguard OSNEM users (e.g., bot detection, toxic content identification,
  content moderation, echo chamber avoidance)
- Case studies of AI application in OSNEM

Online Social Networks and Media is a multidisciplinary journal for the wide community of computer and network scientists working on developing OSNEM platforms and services and using OSNEM as a big data source to mine, learn and model the (online) human behaviour. Manuscripts only based on questionnaires, even focused on the reported use of social media, are outside the scope of the journal. On the other hand, the journal welcomes papers which present analyses based on big data mined from social networks/media.

-----------------------------------------------------------------------------
Schedule 
  Manuscript submission deadline: continuous submission until July 31st, 2024 (*)
  First notification: two months after the submission
  Expected publication: papers are published a few weeks after acceptance.

Guest Editors
  Marco Conti, IIT-CNR, Italy
  Andrea Passarella, IIT-CNR, Italy
------------------------------------------------------------------------------

Instructions for submission

Manuscripts must not have been previously published nor currently under review by other journals or conferences. If prior work was published in a conference, the submitted manuscript should include a substantial extension of at least 35% novel contributions. In this case, authors are also required to submit their published conference articles and a summary document explaining the enhancements made in the journal version.

The submission website for this journal is located at https://www2.cloud.editorialmanager.com/osnem/default2.aspx. Please select ''VSI:AI&OSNEM'' when you reach the ''Article Type'' step in the submission process. To ensure that all manuscripts are correctly identified, for consideration by the special issue, the authors should indicate in the cover letter that the manuscript has been submitted for the special issue on “AI&OSNEM”.

(*) Manuscripts can be submitted continuously until the deadline. Once a paper is submitted, the review process will start immediately. Accepted papers will be published continuously in the journal (in the first issue available as soon as the paper is accepted). All accepted papers will be listed together in an online virtual special issue published in the journal website.

For further information, please contact the guest editors at {m.conti,a.passarella} at iit.cnr.it

**************************************************************
               Political Methodology E-Mail List
   Editors:  Yuan (Cecilia) Sui and Gechun Lin
                  <[log in to unmask]>
**************************************************************
     Send messages to [log in to unmask]
  To join the list, cancel your subscription, or modify
                 your subscription settings visit:

  https://www.cambridge.org/core/membership/spm/mailing-list

**************************************************************

ATOM RSS1 RSS2