Thematic Network Modelling for Digital Ecosystems

数字生态系统主题网络建模

• 批准号: 2596487
• 金额: --
• 依托单位: University of Warwick
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2596487
• 关键词: Thematic; Network; Modelling; Digital; Ecosystems

The contect of the researchThe shift from traditional communication methods towards digital ones brings about massive information dissemination with little to no regulation, making difgital ecosystems and increasingly timely interdisciplinary topic in recent years. Digital ecosystems can include, for example social media platforms and digital markets. Understanding such systems and proposign appropriate policies have therefore become more and more prominent recently. Current computational techniques rarely pay attention to the inherent role each individual/organisation/company's behaviour plays in the ecology from a system-level perspective, such as information creator, propagandist and listener in the online social media, or crucial/peripheral rank each stakeholder posesesses in a digital market. This project therefore would like to build on such traits, especially in the context of multi-sided groups.The aims and objectives of the researchThis project aims at dveloping computational analysis, simulation and intervention of interaction dynamics in digital ecosystems, seeking to answer the following key problems;1. How to assess the inherant role each individual/organisation. complay plays in a system-levale interpretable way.2. Can we make meaningful comparison between milti-sided groups via thier role sturctures and behavioral simiulation.3. To improv the digital ecosystem, what intervention approaches can be proposed based on the analysis above? This will likely make use to the reommendation algorithm.4. What are the scalability limitations of the method above, and can we mitigate them to enable analysis on increasing data sizes (e.g across large population samples or different geographies)?The novelty of the research methodologyThe main novelty in this research is the application of network structure techniques to assess system-level collective behavioral features in digital ecosystems and propose relevant intervention approaches accordingly, particularly relevant with recmmendation algorithms.The potential impact, applications and benefitsIntroducing complex network structures to digital ecosystems can provide an intuitive system-level evaluation of extensive user interaction dynamics. Appropriate intervention methods may be explored to potentially improve digital regilation and policy.How the rsearch relates to the remitThis research is closely related with the EPSRC remit in both its methodology and goal. Complex network modelling as the primary methodology strongly relies on mathematical sciences. The goal is to improve the digital ecosystem, lying in both Digital Economy and ICT (Inofrmation and Communication Technologies).External Partner - StateUP (https://stateup.co/nebula/) - StateUp is a start up company which stands at the crossroads of industry and academia, working on procurement technologies for the publc sector. It will provide me with both internship opportunities and datasets. In details, I can help build Nebula, a repository curated by stateUp that can be used to make recommendations to public bodies seeeking to resolve societal problems at various scales. During this process, I will also have exclusive access to acurated dataser of company profiles.

从传统传播方式向数字传播方式的转变带来了大量的信息传播，几乎没有监管，使数字生态系统成为近年来越来越及时的跨学科课题。数字生态系统可以包括例如社交媒体平台和数字市场。因此，了解这种制度并提出适当的政策，近年来变得越来越突出。目前的计算技术很少注意到每个人/组织/公司的行为在生态系统中发挥的内在作用，从系统层面的角度来看，如信息的创造者，宣传者和听众在网上社交媒体，或关键/外围排名每个利益相关者posesesses在数字市场。因此，本项目希望建立在这样的特点，特别是在多方面的群体背景下。研究的目的和目标本项目旨在发展数字生态系统中交互动力学的计算分析，模拟和干预，寻求回答以下关键问题：1.如何评估每个个人/组织的继承角色。compay以一种系统级可解释的方式发挥作用.我们能否通过角色结构和行为模拟在多方面群体之间进行有意义的比较。3.为了改善数字生态系统，基于上述分析，可以提出哪些干预方法？这可能会利用recommendation算法。4.上述方法的可扩展性限制是什么？我们能否减轻这些限制，以支持对不断增加的数据大小进行分析（例如，跨大人口样本或不同地理位置）？研究方法的新奇本研究的主要新奇在于应用网络结构技术评估数字生态系统中系统级集体行为特征，并相应提出相关干预方法，特别是与recmmendation算法相关的潜在影响，应用和优势将复杂的网络结构引入数字生态系统可以提供一个直观的系统-广泛的用户交互动态的水平评估。适当的干预方法可能会被探索，以潜在地改善数字regilation和政策。研究如何与remitteThis研究是密切相关的EPSRC的职权范围在其方法和目标。复杂网络建模作为主要的方法论，强烈依赖于数学科学。我们的目标是改善数字生态系统，包括数字经济和ICT（信息和通信技术）。外部合作伙伴- StateUP（https：//stateup.co/nebula/）- StateUp是一家处于工业和学术界十字路口的初创公司，致力于为数字经济部门提供采购技术。它将为我提供实习机会和数据集。具体来说，我可以帮助构建Nebula，这是一个由stateUp管理的存储库，可以用来向寻求解决各种规模的社会问题的公共机构提出建议。在此过程中，我也将有独家访问acurated公司简介数据。