|Project's title||Research and develop effective methods to prevent the spread of misinformation on social networks|
|Research hosting institution||Institute of Information Technology|
|Project leader’s name||Assoc. Prof. Nguyen Viet Anh|
|Project duration||01/01/2021 - 31/12/2022|
|Project’s budget||600 million VND|
|Goal and objectives of the project||
- Researching mechanisms and models of spreading information in general and misinformation in particular on online social networks. Identifying and analyzing the characteristics of misinformation, influential factors on social networks (such as individuals, communities) play an important role in disseminating information.
- Propose effective methods and techniques to limit the spread of misinformation. Focusing on the problem in which information is distributed from many sources, on many different topics, the distribution mechanism changes over time, and the constraints on prevention costs must be satisfied.
- Implementing, testing and evaluating the effectiveness of proposed methods on simulated datasets and data from real social networks.
- Publication of research results in SCIE journals
1) Propose a multi-topic information propagation model based on the linear threshold model LT (Linear Threshdl) to solve the problem of information propagation of many topics and many sources.
2) Propose 02 algorithms to detect the source of disseminating information and 04 algorithms to prevent the spread of misinformation on online social networks according to the "Vaccination" approach and the approximation and heuristic algorithms.
3) Training 01 PhD student, 01 MsC student with thesis topics in the research direction of the project.
4) 02 papers in the research direction of the project. In which 01 paper in the SCIE-Q1 journal; 01 paper in Journal of Research and Development on Information and Communication Technology, Vietnam.
1) Develop a pilot program to prevent the spread of misinformation on online social networks.
2) Testing and evaluating the results of running a program to prevent the spread of misinformation on online social networks with the input of real social networks that are filtered for privacy factors
|Novelty and actuality and scientific meaningfulness of the results||
- Propose 02 effective algorithms to detect sources of misinformation on social networks, including: sample-based detection algorithm - SMD (Sampling- based for Misinformation Detection) and detection algorithm based on on the important sample set - ISMD (Important Sampling-based Misinformation Detection).
- Propose a model to solve the problem of spreading misinformation on many topics - MTLT (Multiple Topic Linear Threshold) and 02 effective algorithms following the Vaccination approach, including: Reference algorithm improved IGA (Improved Greedy Algorithm) and GEA (Greedy Expanded Algorithm) greedy algorithms.
- Propose 02 effective algorithms to solve the problem of preventing the spread of misinformation on many topics with time and cost constraints according to approximation and heuristic approaches, including: IGA algorithm and algorithm FIB. These algorithms can be applied to large-scale networks, up to millions of users.
|Products of the project||
- Scientific papers in referred journals (list):
02 papers in the research direction of the project. In which 01 paper in the SCIE-Q1 journal; 01 paper in Journal of Research and Development on Information and Communication Technology, Vietnam.
1. Canh V Pham, Dung V Pham, Bao Q Bui, Anh V Nguyen, “Minimum budget for misinformation detection in online social networks with provable guarantees”. Optim. Lett., pp. 1-30, 2021 (SCIE, Q1).
2. Pham Van Dung, Nguyen Thi Tuyet Trinh, Vu Chi Quang, Ha Thi Hong Van, Nguyen Viet Anh, “Minimum budget to detect misinformation on online social networks, ensuring at least a given threshold is met,” Journal of Research and Development on Information and Communication Technology, Vol. 2021, No 2, 2021.
- Patents (list):
- Technological products (describe in details: technical characteristics, place):
1) Scientific report on methods and techniques to prevent the spread of false information on online social networks.
2) Pilot program to prevent the spread of misinformation on online social networks
3) Documentation of analysis, design, user manual and program installation
4) Program test results report
5) Report on the results of the project
6) Scientific papers (evidences in the report of the project )
7) Training support 01 PhD student, 01 MsC student (evidenced in the report of the project)
|Research area||Proposing implementing on real social networks in Vietnam. |
|Images of project|| |