A Framework for Analyzing Influencer Marketing in Social Networks: Selection and Scheduling of Influencers

Mallipeddi, Rakesh; Kumar, Subodha; Sriskandarajah, Chelliah; Zhu, Yifu

doi:10.2139/ssrn.3255198

Cited by 9 publications

(5 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mallipeddi et al (2018a) use the twitter data to empirically examine the effect of social media tone on engagement. Mallipeddi et al (2018b) extend this study to optimize selection and scheduling of influencers in social marketing. Kumar et al (2017a) study a recent phenomenon of trademarking hashtags in social media.…”

Section: Social Media and Digital Platformsmentioning

confidence: 95%

See 1 more Smart Citation

Research in Operations Management and Information Systems Interface

Kumar

Mookerjee

Shubham

2018

Production and Operations Management

Self Cite

160

128

View full text Add to dashboard Cite

Owing to its multidisciplinary nature, the operations management (OM) and information systems (IS) interface distinguishes itself from the individually focused perspective of both fields. The number and depth of contributions in this department can help both disciplines advance to better address important theoretical and practical challenges of the business world. In this paper, we study the characteristics of problems at the interface between OM and IS, and review past work that has been instrumental in setting the tone and direction of research at this interface. We extend our discussion to provide directions for future research at the OM and IS interface in the domains such as smart city management, healthcare, deep learning and artificial intelligence, fintech and blockchain, Internet of Things and Industry 4.0, and social media and digital platforms.

show abstract

Section: Social Media and Digital Platformsmentioning

confidence: 95%

“…Mallipeddi et al. () extend this study to optimize selection and scheduling of influencers in social marketing. Kumar et al.…”

Section: The Path Forwardmentioning

confidence: 98%

Research in Operations Management and Information Systems Interface

Kumar

Mookerjee

Shubham

2018

Production and Operations Management

Self Cite

160

128

View full text Add to dashboard Cite

show abstract

“…Lagree et al in 2017 proposed a diffusion model to overcome online influence marketing with persistence (OIMP) problem and worked on real data gathered from twitter. Most recent work in this direction is done by (Mallipeddi et al, 2018). This work has been done in two directions-selection of influencers and scheduling of influencers' ads on real data from twitter.…”

Section: Identified Knowledge Gaps and Research Contributionsmentioning

confidence: 99%

Measuring social media influencer index- insights from facebook, Twitter and Instagram

Arora

Bansal²,

Kandpal³

et al. 2019

Journal of Retailing and Consumer Services

435

198

View full text Add to dashboard Cite

The growth of social media has completely revamped the way people interact, communicate and engage. These platforms play a key role in facilitating greater outreach and influence. This study proposes a mechanism for measuring the influencer index across popular social media platforms including Facebook, Twitter, and Instagram. A set of features that determine the impact on the consumers are modelled using a regression approach. The underlying machine learning algorithms including Ordinary Least Squares (OLS), K-NN Regression (KNN), Support Vector Regression (SVR), and Lasso Regression models are adapted to compute a cumulative score in terms of influencer index. Findings indicate that engagement, outreach, sentiment, and growth play a key role in determining the influencers. Further, the ensemble of the four models resulted in the highest accuracy of 93.7% followed by the KNN regression with 93.6%. The study has implications across various domains of e-commerce, viral marketing, social media marketing and brand management wherein identification of key information propagators is essential. These influencer indices may further be utilized by e-commerce portals and brands for the purpose of social media promotion and engagement for larger outreach.

show abstract

“…2018, Mallipeddi et al. 2021, Qiu and Whinston 2017). Social technologies not just created new business models and new industries, they revolutionized the nature of how businesses operate and changed the landscape of industry competition and operations in supply chain (Cui et al.…”

Section: Introductionmentioning

confidence: 99%