Research on opinion polarization by big data analytics capabilities in online social networks

Xing, Yunfei; Wang, Xiwei; Qiu, Chengcheng; Li, Yueqi; He, Wu

doi:10.1016/j.techsoc.2022.101902

Cited by 37 publications

(10 citation statements)

References 73 publications

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“…Noteworthy, in social studies parameter σ (or its simpler version σ = 1 N ∑ i σ i ) is often interpreted as "social polarization", that accounts for two opposite opinions inherent to the network actors, e.g. [39][40][41] . The polarized state appears as a result of agents' homophily and echo chamber effect and features bimodal distribution for agents' opinions 42 .…”

Section: Nias Decision-making Evaluationmentioning

confidence: 99%

Quantum-inspired modeling of distributed intelligence systems with artificial intelligent agents self-organization

Alodjants,

Tsarev,

Avdyushina

et al. 2024

Preprint

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Distributed intelligence systems (DIS) containing natural (NIA) and artificial (AIA) intelligence agents of decision making (DM) belong to interdisciplinary areas of promising studies aimed at digitalization of routine processes in industry, economy, management, and everyday life. In this work, we suggest a novel quantum-inspired approach to study crucial features of DIS consisting of NIAs (users) and AIAs (digital assistants) that possess self-organization within a complex network. We propose a mapping procedure for Russell’s valence-arousal circumplex model onto an effective quantum-like two-level system to characterize a NIA cognitive system in a simple DM process. We demonstrate that conditions for opinion formation and social impact in a DIS are relevant to the second-order (laser-like) phase transition that establishes a nonvanishing average information field in the DIS, which is reminiscent of the social laser phenomenon that may appear in social networks. We demonstrate the complex behavior of social impact in the DIS that implies the hierarchical formation of opinion leaders in the network, which we elucidated using the eigenvector centrality criterion. We introduce a set of cooperativity parameters for the users, which play a significant role in DIS features. Cooperativity parameters reveal how frequently AIAs and NIAs communicate with each other accounting for their facilities in information exchange. We show that at weak AIA -- NIA coupling many uncertainties in the DIS complicate a certain (non-zero) opinion formation for DM agents. We offer an adaptive approach to increase the users' impact by establishing a network-dependent coupling rate with their digital assistants. In this case, the mechanism of AIA control helps resolve the DM process in the presence of some uncertainties evoked by the variety of users' preferences. Our findings open new prospectives in different areas where AIAs represent useful teammates in solving common problems with humans in the framework of network organizations.

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Section: Nias Decision-making Evaluationmentioning

confidence: 99%

Quantum-inspired modeling of distributed intelligence systems with artificial intelligent agents self-organization

Alodjants,

Tsarev,

Avdyushina

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…In the current digital age, social media, such as Twitter, have become a major tool for the diffusion and distribution of information [ [22] , [23] , [24] , [25] , [26] ]. There was an alarming increase in tweets mentioning COVID-19 over the days following the COVID-19 outbreak [ 27 ].…”

Section: Literature Reviewmentioning

confidence: 99%

From Heroes to Scoundrels: Exploring the effects of online campaigns celebrating frontline workers on COVID-19 outcomes

Polyzos

Fotiadis

Huan

2023

Technology in Society

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“…Weiss and Nemeczek [43] proposed an automatic text analysis method based on unsupervised latent Dirichlet assignment (LDA) topic modelling and dictionary-based emotion analysis. Xing et al [44] used social network analysis (SNA), machine learning, text clustering, content analysis, and other methods for text mining. Gyódi et al [45] proposed an innovative text mining method to support policy analysts in identifying, defining, and selecting problems.…”

Section: Literature Review and Theoreticalmentioning

confidence: 99%

Quantitative Evaluation of Big Data Development Policy: Text Data Analysis Based on Coword Network and Policy Tools

Hong

2022

Mathematical Problems in Engineering

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In the context of the continuous promotion of China’s big data development strategy, this paper quantitively analyses China’s existing national-level big data policies from the perspective of policy instruments and coword networks, discusses the rationality of existing policies, explores ways to improve policies, and provides a reference for the innovation of China’s big data policies. This paper carries out a quantitative textual analysis of China’s national big data policy from the perspective of policy instruments using word frequency analysis to obtain a keyword coword matrix and visualization analysis tools to obtain a coword network. This paper further studies the network node characteristics and structure using social network analysis methods, including degree centrality, clustering analysis, and multidimensional scale analysis, to identify the policy structure and characteristics. Improving big data policy requires improvements in policy instruments on the supply side, resolving existing policy gaps, and strengthening coordination with other policies.

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Research on opinion polarization by big data analytics capabilities in online social networks

Cited by 37 publications

References 73 publications

Quantum-inspired modeling of distributed intelligence systems with artificial intelligent agents self-organization

Quantum-inspired modeling of distributed intelligence systems with artificial intelligent agents self-organization

From Heroes to Scoundrels: Exploring the effects of online campaigns celebrating frontline workers on COVID-19 outcomes

Quantitative Evaluation of Big Data Development Policy: Text Data Analysis Based on Coword Network and Policy Tools

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