Jove
Visualize
お問い合わせ
JoVE
x logofacebook logolinkedin logoyoutube logo
JoVEについて
概要リーダーシップブログJoVEヘルプセンター
著者向け
出版プロセス編集委員会範囲と方針査読よくある質問投稿
図書館員向け
推薦の声購読アクセスリソース図書館諮問委員会よくある質問
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experimentsアーカイブ
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教員リソースセンター教員サイト
利用規約
プライバシーポリシー
ポリシー

関連する概念動画

Social Exchange Theory02:06

Social Exchange Theory

39.4K
We have discussed why we form relationships, what attracts us to others, and different types of love. But what determines whether we are satisfied with and stay in a relationship? One theory that provides an explanation is social exchange theory. According to social exchange theory, we act as naïve economists in keeping a tally of the ratio of costs and benefits of forming and maintaining a relationship with others (Rusbult & Van Lange, 2003).
39.4K
Social Exchange Theory01:26

Social Exchange Theory

391
As formulated by John Thibaut and Harold Kelley, Social Exchange Theory explains human relationships as economic-like exchanges that maximize rewards and minimize costs. This theory suggests that individuals engage in relationships to gain benefits and reduce burdens, similar to economic transactions. It has been widely applied to various types of relationships, including romantic, professional, and social interactions.Rewards and Costs in RelationshipsRelationship rewards include emotional...
391
Social Foundations of Self IV: Self in Digital Communication01:30

Social Foundations of Self IV: Self in Digital Communication

166
Since the early 2000s, computer-mediated communication (CMC) has grown rapidly, playing a crucial role in self-development. A key distinction between CMC and real-life interactions is the lack of a physically present partner. This absence makes non-verbal cues such as facial expressions, body language, and paralinguistic signals unavailable in CMC platforms like email, instant messaging, or social media. The lack of these cues can create ambiguity and complicate how feedback is interpreted.The...
166
Relationship Formation02:12

Relationship Formation

45.2K
What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
45.2K
Social Identity01:29

Social Identity

238
Social identity constitutes a significant aspect of an individual’s self-concept, shaped by membership in various social groups, including gender, nationality, ethnicity, sexual orientation, and political affiliation. Individuals associate specific traits with particular social groups, leading to internalization of these traits. For example, musicians are often perceived as creative, while women are frequently associated with nurturing tendencies. Once individuals identify with a...
238
Group Polarization01:01

Group Polarization

38.4K
Group polarization is the strengthening of an original group attitude following the discussion of views within a group (Teger & Pruitt, 1967). That is, if a group initially favors a viewpoint, after discussion the group consensus is likely a stronger endorsement of the viewpoint. Conversely, if the group was initially opposed to a viewpoint, group discussion would likely lead to stronger opposition.
38.4K

こちらも読む

関連記事

共著者、ジャーナル、引用グラフによってこの研究に関連する記事。

並び替え
Same author

Continuous growth of social polarization for scale-free networks.

Chaos (Woodbury, N.Y.)·2026
Same author

Estimating an affine term structure model of interest rates with correlated noise.

PloS one·2025
Same author

Reconstructing community structure of online social network via user opinions.

Chaos (Woodbury, N.Y.)·2022
Same author

Optimal resilience of modular interacting networks.

Proceedings of the National Academy of Sciences of the United States of America·2021
Same author

Selective transport capacity for K<sup>+</sup> over Na<sup>+</sup> is linked to the expression levels of PtSOS1 in halophyte Puccinellia tenuiflora.

Functional plant biology : FPB·2020
Same author

A dual-gas sensor for simultaneous detection of methane and acetylene based on time-sharing scanning assisted wavelength modulation spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy·2020

関連する実験動画

Updated: Jan 14, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

5.5K

リーダー主導のソーシャルネットワーク再構築

Rende Li1,2, Qiang Guo2, Jianguo Liu3

  • 1Library, University of Shanghai for Science and Technology, Shanghai 200093, China.

Chaos (Woodbury, N.Y.)
|January 13, 2026
PubMed
まとめ
この要約は機械生成です。

中心性の低いリーダーは、情報的多様性を維持することにより、ネットワーク再構築の精度を向上させ、従来の戦略に挑戦する。最適なパフォーマンスは、寛容なコミュニティにおける保守的で頑固なリーダーによって達成される。

キーワード:
ソーシャルネットワークネットワーク再構築意見ダイナミクスリーダーシップ中心性情報多様性

さらに関連する動画

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

6.3K
The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.8K

関連する実験動画

Last Updated: Jan 14, 2026

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
08:53

Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community

Published on: May 31, 2019

5.5K
A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants
06:28

A Networked Desktop Virtual Reality Setup for Decision Science and Navigation Experiments with Multiple Participants

Published on: August 26, 2018

6.3K
The HoneyComb Paradigm for Research on Collective Human Behavior
06:48

The HoneyComb Paradigm for Research on Collective Human Behavior

Published on: January 19, 2019

9.8K

科学分野:

  • 計算社会科学
  • ネットワーク科学
  • 意見ダイナミクス

背景:

  • ネットワーク再構築における意見リーダーの影響を理解することは重要です。
  • 既存の戦略は、しばしば中心性の高いノードを優先します。

研究 の 目的:

  • 意見リーダーの特性がネットワーク再構築の精度にどのように影響するかを調査すること。
  • 意見ダイナミクスと圧縮センシングを統合する新しいフレームワークを開発すること。

主な方法:

  • リーダー主導の意見ダイナミクスと圧縮センシングを組み合わせたフレームワークを開発しました。
  • ノードの中心性、初期意見、受容率、意見の均一性を実験的に評価しました。
  • 3つの実世界のネットワークと3つの合成ネットワークでテストしました。

主要な成果:

  • 中心性の低いリーダーは、再構築において中心性の高いノードよりも一貫して優れたパフォーマンスを発揮します。
  • 高い中心性は、本質的な情報的多様性を低下させる急速な意見収束につながります。
  • 非常に保守的（o=0.0）で頑固（α=1.0）なリーダーは、適度な寛容性（ε=0.5）を持つコミュニティで最適なパフォーマンスを発揮します。

結論:

  • ネットワーク再構築における効果的な意見リーダーシップは、構造的重要性だけでなく、ダイナミクス固有の要因に依存します。
  • 発見は、従来の中心性ベースのリーダー選択に挑戦します。
  • マーケティング、公衆衛生、危機コミュニケーションへの影響。