最大限度地提高社交网络中观点文章的多样性和说服力

IF 0.9 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Journal of Combinatorial Optimization Pub Date : 2024-11-01 DOI:10.1007/s10878-024-01226-7
Liman Du, Wenguo Yang, Suixiang Gao
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引用次数: 0

摘要

社交媒体平台为个人与他人保持联系、分享观点和参与不同问题的讨论创造了新的途径。传统上由社会科学研究的观点动态已引起其他领域科学家的关注。舆论的形成和演变是一个复杂的过程,受到不同因素相互作用的影响,这些因素包括社交网络中的同伴互动以及每个人所接触到的信息的多样性。此外,补充信息也会对观点的形成和演变起到重要的推动作用。由于网络社交平台的特点,人们可以随时轻松结束现有的追随者-被追随者关系或停止与朋友的互动。在此基础上,我们提出了同时考虑舆论和关系动态的 OG-IC 模型。它不仅考虑了好友的直接影响,还强调了当个人接触到新观点时群体的间接影响。而且,它允许代表社交网络用户的节点略微调整自己的观点,有时还会重新定义朋友关系。本文提出了一个社交网络中的新问题,其目的是同时最大化个人获取补充信息的多样性和补充信息对个人现有观点的影响。该问题被证明是 NP 难问题,其目标函数既不是亚模态的,也不是超模态的。不过,我们基于三明治框架设计了一种具有近似比率保证的算法。并在合成数据集和实际数据集上实验证明了我们算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Maximizing diversity and persuasiveness of opinion articles in social networks

Social-media platforms have created new ways for individuals to keep in touch with others, share their opinions and join the discussion on different issues. Traditionally studied by social science, opinion dynamic has attracted the attention from scientists in other fields. The formation and evolution of opinions is a complex process affected by the interplay of different elements that incorporate peer interaction in social networks and the diversity of information to which each individual is exposed. In addition, supplementary information can have an important role in driving the opinion formation and evolution. And due to the character of online social platforms, people can easily end an existing follower-followee relationship or stop interacting with a friend at any time. Taking a step in this direction, we propose the OG–IC model which considers the dynamic of both opinion and relationship in this paper. It not only considers the direct influence of friends but also highlights the indirect effect of group when individuals are exposed to new opinions. And it allows nodes which represent users of social networks to slightly adjust their own opinion and sometimes redefine friendships. A novel problem in social network whose purpose is simultaneously maximizing both the diversity of supplementary information that individuals access to and the influence of supplementary information on individual’s existing opinion is formulated. This problem is proved to be NP-hard and its objective function is neither submodular nor supermodular. However, an algorithm with approximate ratio guarantee is designed based on the sandwich framework. And the effectiveness of our algorithm is experimentally demonstrated on both synthetic and real-world data sets.

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来源期刊
Journal of Combinatorial Optimization
Journal of Combinatorial Optimization 数学-计算机:跨学科应用
CiteScore
2.00
自引率
10.00%
发文量
83
审稿时长
6 months
期刊介绍: The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering. The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.
期刊最新文献
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