Opinion-Based Co-Occurrence Network for Identifying the Most Influential Product Features

Jayaraman, Ashok Kumar; Abirami, S.

doi:10.36909/jer.v8i4.8369

Cited by 4 publications

(2 citation statements)

References 41 publications

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“…This method enables both multiscale graph representation and a locally comprehensible layout. Furthermore, it visualizes directed and large graphs in multiple dimensions with a navigational ability (Harel and Koren, 2006; Jayaraman and Abirami, 2020).…”

Section: Methodsmentioning

confidence: 99%

Exploring the diffusion of digital fashion and influencers' social roles in the Metaverse: an analysis of Twitter hashtag networks

Kim,

Chakraborty

2023

INTR

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PurposeThe study aims to explore the digital fashion trend within the Metaverse, characterized by non-fungible tokens (NFTs), across Twitter networks. Integrating theories of diffusion of innovation, two-step flow of communication and self-efficacy, the authors aimed to uncover the diffusion structure and the influencer's social roles undertaken by social entities in fostering communication and collaboration for the advancement of Metaverse fashion.Design/methodology/approachSocial network analysis examined the critical graph metrics to profile, visualize, and cluster the unstructured network data. The authors used the NodeXL program to analyze two hashtag keyword networks, “#metaverse fashion” and “#metawear,” using Twitter API data. Cluster, semantic, and time series analyses were performed to visualize the contents and contexts of communication and collaboration in the diffusion of Metaverse fashion.FindingsThe results unraveled the “broadcast network” structure and the influencers' social roles of opinion leaders and market mavens within Twitter's “#metaverse fashion” diffusion. The roles of innovators and early adopters among influencers were comparable in collaborating within the competition venues, promoting awareness and participation in digital fashion diffusion during specific “fad” periods, particularly when digital fashion NFTs and cryptocurrencies became intertwined with the competition in the Metaverse.Originality/valueThe study contributed to theory building by integrating three theories, emphasizing effective communication and collaboration among influencers, organizations, and competition venues in broadcasting digital fashion within shared networks. The validation of multi-faceted Social Network Analysis was crucial for timely insights, highlighting the critical digital fashion equity in capturing consumers' attention and driving engagement and ownership of Metaverse fashion.

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Section: Methodsmentioning

confidence: 99%

Exploring the diffusion of digital fashion and influencers' social roles in the Metaverse: an analysis of Twitter hashtag networks

Kim,

Chakraborty

2023

INTR

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“…Based on past research, this study divides consumer motivations to participate in brand communities into three types (Han et al, 2019;: function-driven factors, society-driven factors, and emotion-driven factors. Function-driven factors drive people to seek information (Kuang et al, 2019), society-driven factors involve people's desire to express themselves and seek friendship, and emotion-driven factors refer to people's instincts to share their emotions (Malthouse et al, 2016;Jayaraman and Abirami, 2020). Although there might be other factors, we focus on these three types of factors according to past research.…”

Section: Motivations Of Consumers' Participation In Brand Communitiesmentioning

confidence: 99%

Do Product Characteristics Affect Customers’ Participation in Virtual Brand Communities? An Empirical Study

ShiYong

Wang

et al. 2022

Front. Psychol.

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The virtual brand community has become an important marketing tool for companies. A successful brand community marketing strategy should attract a large number of consumers. Although past studies have revealed consumer motivations for participating in virtual brand communities, they fail to answer an important question: Why is it so easy for some virtual brand communities to attract users while others have such difficulty? In this study, product characteristics are hypothesized to be important factors that determine consumer motivation to participate in brand communities. Product characteristics (e.g., product complexity, product symbolism, and product satisfaction) can directly affect how actively consumers participate in brand communities. The results of questionnaires show that product complexity, product symbolism, and product satisfaction have a positive influence on consumers’ willingness to participate in brand communities. Notably, the duration of product use has a regulating effect on the influence of product satisfaction and product symbolism. A long period of product use weakens the influence of product satisfaction on consumers’ willingness to participate in brand communities. On the contrary, a long period of product use strengthens the influence of product symbolism on consumers’ willingness to participate in brand communities. This study enriches the literature on brand community participation and has implications for companies that aim to utilize brand communities for marketing.

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Ensemble application of bidirectional LSTM and GRU for aspect category detection with imbalanced data

Kumar

Abirami

2021

Neural Comput & Applic

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Opinion-Based Co-Occurrence Network for Identifying the Most Influential Product Features

Cited by 4 publications

References 41 publications

Exploring the diffusion of digital fashion and influencers' social roles in the Metaverse: an analysis of Twitter hashtag networks

Exploring the diffusion of digital fashion and influencers' social roles in the Metaverse: an analysis of Twitter hashtag networks

Do Product Characteristics Affect Customers’ Participation in Virtual Brand Communities? An Empirical Study

Ensemble application of bidirectional LSTM and GRU for aspect category detection with imbalanced data

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