Algorithms for Online Influencer Marketing

Lagrée, Paul; Cappé, Olivier; Cautis, Bogdan; Maniu, Silviu

doi:10.1145/3274670

Cited by 32 publications

(26 citation statements)

References 36 publications

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“…Social and influencer marketing are arguably the hottest concepts in online advertising at the moment [ 33 ]. Most organisations that advertise online must have a “social” strategy [ 34 ]. Deploying influencers, such as Instafamous people, for branding has become an important aspect of social media marketing campaigns [ 35 ].…”

Section: Literature Reviewmentioning

confidence: 99%

Customer review or influencer endorsement: which one influences purchase intention more?

Dwidienawati

Tjahjana

Abdinagoro

et al. 2020

Heliyon

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Informativeness plays a key role in online shopping decisions. Potential customers usually collect useful information and do a comparison before considering the purchase. Electronic word-of-mouth (eWOM) is considered a reliable source of information. Customer reviews and influencer reviews can be considered eWOM. They represent customers' sharing of experience and evaluation of a product or service with other potential shoppers. There is abundant evidence concerning the influence of eWOM on purchase intention. However, there are few studies on influencer reviews and purchase intention. This study aims to investigate the impact of customer review and influencer review to purchase intention and the mediating role of trust to those relationship. A quantitative experimental study (2 Â 1) was conducted. Two hundred respondents from three cities in Greater Jakarta were divided into two groups to self-rate their opinion on customer review, influencer review, trust and purchase intention. Data collected was analysed PLS using SmartPLS. The study results showed that influencer review has a positive impact on purchase intention. On the other hand, customer review failed to show its influence. Trust as a moderating variable was also not validated in this study.

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Section: Literature Reviewmentioning

confidence: 99%

Customer review or influencer endorsement: which one influences purchase intention more?

Dwidienawati

Tjahjana

Abdinagoro

et al. 2020

Heliyon

View full text Add to dashboard Cite

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“…At present, influencer marketing is an important tool to influence buying behaviour and can be defined as the process of exploring, identifying, supporting and engaging people involved in high impact conversations. It is an important form of online marketing, in which the marketers target a sub-population of influential people, instead of the entire base of potential buyers [8].…”

Section: Introductionmentioning

confidence: 99%

The role of influencers in the consumer decision-making process

Žák

Hasprová

2020

SHS Web Conf.

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In the contemporary globalised markets opinion leaders play a vital role in the process of the purchasing decision-making of consumers. Thanks to their individual skills, specific knowledge or their personality, opinion leaders have a direct or indirect influence on the attitudes and decisions of consumers. In the contemporary globalised marketing using social media, this role is taken over by the influencers who affect consumers with their thoughts, attitudes and opinions and thus, significantly influence trends in demand for particular products. Over the recent years, influencer marketing has become increasingly popular, representing a specific type of social media marketing. The aim of this scientific contribution is the systematization of knowledge about the position and roles of influencers as opinion leaders in the social media environment in order to identify their typology, influence factors and the intensity of their impact on consumer decision making process, based on the comparison of knowledge from the results of global research studies and the quantitative online research study processed by authors. The findings of the survey showed that the promotion of some products through influencers may be more advantageous than others. Influencers will have the greatest impact when buying clothes, shoes, cosmetics and, surprisingly, services. Meanwhile, people rely heavily on other factors to buy food, jewellery and electronics, but it is not excluded that influencer marketing could affect them as well.

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“…Lagrée et al [24] proposed a new formulation for the problem of influence maximization called online influence maximization with persistence ''OIMP'' that tries to target a subpopulation from the graph without making any prior assumption on the used diffusion model. Then, they proposed an estimator method that can be reached from a given influential node based on real Twitter data.…”

Section: Related Workmentioning

confidence: 99%

Influence Maximization Based Global Structural Properties: A Multi-Armed Bandit Approach

et al. 2019

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The influence maximization problem is defined by identifying the seed set that has the most influence on other users in the network, which when selected, the cascading process reaches a large number of users. We use a greedy algorithm and an epsilon-greedy algorithm from the MAB models in this work, unlike prior works that used the MAB models to quantify the unknown propagation probability in the diffusion models. In this paper, we did not also make any assumption regarding the diffusion models and tries to learn to identify the most influential users based on designed reward function ''hybrid edge strength-similarity'' using global centrality measures and by trying to find a tradeoff between exploitation and exploration strategies. The new proposed reward function initializes the MAB algorithms using global characteristics that quantify the strength of each arm (edge). The proposed reward will feed algorithms from MAB models uses hybridization of edge betweenness centrality and Jaccard similarity measures with some level of participation of each measure. Then, three algorithms are proposed for the extraction of relevant influencers, namely: SRI-CGSS FEXPL-GREEDY) algorithm which almost exploiting the best arm; the SRI_CGSS FEXPR-GREEDY which is almost exploring; and the SRI-MAB-GREEDY algorithm that alternate between exploring and exploiting the best arms. We conduct extensive experiments on a large-scale graph in terms of influence spread, efficiency performance in terms of running time and space complexity, and how the reward parameters impact cumulative regret.

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Algorithms for Online Influencer Marketing

Cited by 32 publications

References 36 publications

Customer review or influencer endorsement: which one influences purchase intention more?

Customer review or influencer endorsement: which one influences purchase intention more?

The role of influencers in the consumer decision-making process

Influence Maximization Based Global Structural Properties: A Multi-Armed Bandit Approach

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