NDLI: Link injection for boosting information spread in social networks

Content Provider	Springer Nature Link
Author	Antaris, Stefanos Rafailidis, Dimitrios Nanopoulos, Alexandros
Copyright Year	2014
Abstract	Social media have become popular platforms for spreading information. Several applications, such as ‘viral marketing’, pause the requirement for attaining large-scale information spread in the form of word-of-mouth that reaches a large number of users. In this paper, we propose a novel method that predicts new social links that can be inserted among existing users of a social network, aiming directly at boosting information spread and increasing its reach. We refer to this task as ‘link injection’, because unlike most existing people-recommendation methods, it focuses directly on information spread. A set of candidate links for injection is first predicted in a collaborative-filtering fashion, which generates personalized candidate connections. We select among the candidate links a constrained number that will be finally injected based on a novel application of a score that measures the importance of nodes in a social graph, following the strategy of injecting links adjacent to the most important nodes. The proposed method is suitable for real-world applications, because the injected links manage to substantially increase the reach of information spread by controlling at the same time the number of injected links not to affect the user experience. We evaluate the performance of our proposed methodology by examining several real data sets from social networks under several distinct factors. The experimentation demonstrates the effectiveness of our proposed method, which increases the spread by more than a twofold factor by injecting as few as half of the existing number of links.
Starting Page	1
Ending Page	16
Page Count	16
File Format	PDF
ISSN	18695450
Journal	Social Network Analysis and Mining
Volume Number	4
Issue Number	1
e-ISSN	18695469
Language	English
Publisher	Springer Vienna
Publisher Date	2014-11-15
Publisher Place	Vienna
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Information spread Social networks Viral marketing Link injection Data Mining and Knowledge Discovery Complex Networks Game Theory, Economics, Social and Behav. Sciences Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law Methodology of the Social Sciences
Content Type	Text
Resource Type	Article
Subject	Information Systems Human-Computer Interaction Communication Computer Science Applications Media Technology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A scalable heuristic for viral marketing under the tipping model

Application of data mining methods for link prediction in social networks

Link prediction in directed social networks

Revenue maximization in social networks through discounting

The spread of media content through blogs

On finding small sets that influence large networks

Evaluation framework for social media brand presence

Social media analysis and summarization for opinion mining: a business case study

Supervised methods for multi-relational link prediction

Link injection for boosting information spread in social networks

Similar Documents

A scalable heuristic for viral marketing under the tipping model

Application of data mining methods for link prediction in social networks

Link prediction in directed social networks

Revenue maximization in social networks through discounting

The spread of media content through blogs

On finding small sets that influence large networks

Evaluation framework for social media brand presence

Social media analysis and summarization for opinion mining: a business case study

Supervised methods for multi-relational link prediction

Link injection for boosting information spread in social networks