scispace - formally typeset
Search or ask a question
Journal ArticleDOI

Influencer Marketing: How Message Value and Credibility Affect Consumer Trust of Branded Content on Social Media

12 Feb 2019-Journal of Interactive Advertising (Routledge)-Vol. 19, Iss: 1, pp 58-73
TL;DR: In this paper, preliminary research involves preliminary research to understand the mechanism by which influencer marketing affects the effectiveness of influencer campaigns, and the results show that the effect of influencers' marketing on the performance of online advertising has been studied.
Abstract: In the past few years, expenditure on influencer marketing has grown exponentially. The present study involves preliminary research to understand the mechanism by which influencer marketing affects...
Citations
More filters
Journal ArticleDOI
TL;DR: In this article, the authors performed a communication analysis of data from the social network Twitter, which included 666,178 messages posted by 168,134 individual users between 2019 and 2020 on Twitter and found that users most commonly associate healthy food with a healthy lifestyle, diet, and fitness.
Abstract: Online social networks have become an everyday aspect of many people's lives. Users spend more and more time on these platforms and, through their interactions on social media platforms, they create active and passive digital footprints. These data have a strong potential in many research areas; indeed, understanding people's communication on social media is essential for understanding their attitudes, experiences, behaviors and values. Researchers have found that the use of social networking sites impacts eating behavior; thus, analyzing social network data is important for understanding the meaning behind expressions used in the context of healthy food. This study performed a communication analysis of data from the social network Twitter, which included 666,178 messages posted by 168,134 individual users. These data comprised all tweets that used the #healthyfood hashtag between 2019 and 2020 on Twitter. The results revealed that users most commonly associate healthy food with a healthy lifestyle, diet, and fitness. Foods associated with this hashtag were vegan, homemade, and organic. Given that people change their behavior according to other people's behavior on social networks, these data could be used to identify current and future associations with current and future perceptions of healthy food characteristics.

15 citations

Proceedings ArticleDOI
30 Nov 2021
TL;DR: In this article, the authors conceptualized and validated the concept of customer engagement with a social media post, proposing a research model which investigates the effects of popularity, discourse logic and argument frame on customer engagement on social media posts.
Abstract: More than 4 billion unique users are now using different social media platforms. This provides firms with a new avenue to connect and converse with their targeted customers in a dialogue fashion and create better customer engagement. Although customer engagement has been studied, no study to date has focused on the concept of customer engagement in social media through the lens of users' participation in (co)creation of content on social media. To that end, this study strives to conceptualize and validate the concept of customer engagement with a social media post, proposing a research model which investigates the effects of popularity, discourse logic and argument frame on customer engagement with a social media post. This study also investigates to what extent those effects vary by the product lifecycle stage and social media platform type, using secondary data extracted from Instagram and Twitter on a group of products (i.e., vehicles) at different lifecycle stages to address its research objective. This study's findings would help firms make better decisions on enhancing their customer engagement on social media platforms.

15 citations

Journal ArticleDOI
Kübra Aşan1
TL;DR: In this paper, the authors explain the impacts of travel influencers on their users' travel behavior and their overall well-being, and propose a travel influencer-based approach.
Abstract: Social media influencer is one of the new concepts that emerged with the development of information technologies and new media. The study aims to explain the impacts of travel influencers on their ...

15 citations


Cites background from "Influencer Marketing: How Message V..."

  • ...As consumers are skeptical of traditional marketing methods, they are likely to pay more attention to and be influenced by influencers, with whom they can communicate via social networks (Lou & Yuan, 2019; Xiao et al., 2018)....

    [...]

  • ...Influencers stamp their posts with personal aesthetic touches and personality twists, which usually create an enjoyable experience (Lou & Yuan, 2019)....

    [...]

  • ...The literature points to the trustworthiness and expertise of influencers in explaining their credibility (Lou & Yuan, 2019)....

    [...]

  • ...Lou and Yuan (2019) suggested that a credibility model included trustworthiness, expertise, similarity, and attractiveness variables....

    [...]

  • ...Also, attractiveness can be considered a sub-factor included in influencers’ source reliability models (Lou & Yuan, 2019)....

    [...]

Journal ArticleDOI
TL;DR: In this article , the authors conceptualized and validated the concept of customer engagement with a social media post, proposing a research model which investigates the effects of popularity, discourse logic and argument frame on customer engagement on social media posts.

15 citations

Proceedings ArticleDOI
20 Apr 2020
TL;DR: A multimodal deep learning model that uses text and image information from social media posts to classify influencers into specific interests/topics and uses the attention mechanism to select the posts that are more relevant to the topics of influencers, thereby generating useful influencer representations.
Abstract: Influencer marketing has become a key marketing method for brands in recent years. Hence, brands have been increasingly utilizing influencers’ social networks to reach niche markets, and researchers have been studying various aspects of influencer marketing. However, brands have often suffered from searching and hiring the right influencers with specific interests/topics for their marketing due to a lack of available influencer data and/or limited capacity of marketing agencies. This paper proposes a multimodal deep learning model that uses text and image information from social media posts (i) to classify influencers into specific interests/topics (e.g., fashion, beauty) and (ii) to classify their posts into certain categories. We use the attention mechanism to select the posts that are more relevant to the topics of influencers, thereby generating useful influencer representations. We conduct experiments on the dataset crawled from Instagram, which is the most popular social media for influencer marketing. The experimental results show that our proposed model significantly outperforms existing user profiling methods by achieving 98% and 96% accuracy in classifying influencers and their posts, respectively. We release our influencer dataset of 33,935 influencers labeled with specific topics based on 10,180,500 posts to facilitate future research.

15 citations


Cites background from "Influencer Marketing: How Message V..."

  • ...3380052 to promote brand awareness and advertise products to social networks of influencers [13, 17, 22, 31], who have ‘influence’ over a large number of followers [3, 4], since customers are often more likely to trust influencers’ recommendations than brands’ advertisements [5, 26, 31]....

    [...]

  • ...Also, previous studies on influencer marketing mostly relied on small datasets that are acquired through surveys of influencers [8, 11, 22] or finding a few influencers on Instagram [20, 29] due to lack of available influencer data....

    [...]

  • ...Due to its popularity, brands tend to increase their budgets for influencer marketing [21], and researchers have started studying various aspects of influencer marketing [8, 11, 20, 22, 29, 33]....

    [...]

  • ...Lou and Yuan [22] presented that influencers’ trustworthiness, attractiveness, and similarity to their followers positively influence on expanding brand awareness and increase purchase intentions....

    [...]

References
More filters
Journal ArticleDOI
01 Jan 1973
TL;DR: In this paper, a six-step framework for organizing and discussing multivariate data analysis techniques with flowcharts for each is presented, focusing on the use of each technique, rather than its mathematical derivation.
Abstract: Offers an applications-oriented approach to multivariate data analysis, focusing on the use of each technique, rather than its mathematical derivation. The text introduces a six-step framework for organizing and discussing techniques with flowcharts for each. Well-suited for the non-statistician, this applications-oriented introduction to multivariate analysis focuses on the fundamental concepts that affect the use of specific techniques rather than the mathematical derivation of the technique. Provides an overview of several techniques and approaches that are available to analysts today - e.g., data warehousing and data mining, neural networks and resampling/bootstrapping. Chapters are organized to provide a practical, logical progression of the phases of analysis and to group similar types of techniques applicable to most situations. Table of Contents 1. Introduction. I. PREPARING FOR A MULTIVARIATE ANALYSIS. 2. Examining Your Data. 3. Factor Analysis. II. DEPENDENCE TECHNIQUES. 4. Multiple Regression. 5. Multiple Discriminant Analysis and Logistic Regression. 6. Multivariate Analysis of Variance. 7. Conjoint Analysis. 8. Canonical Correlation Analysis. III. INTERDEPENDENCE TECHNIQUES. 9. Cluster Analysis. 10. Multidimensional Scaling. IV. ADVANCED AND EMERGING TECHNIQUES. 11. Structural Equation Modeling. 12. Emerging Techniques in Multivariate Analysis. Appendix A: Applications of Multivariate Data Analysis. Index.

37,124 citations

Journal ArticleDOI
TL;DR: This chapter discusses Structural Equation Modeling: An Introduction, and SEM: Confirmatory Factor Analysis, and Testing A Structural Model, which shows how the model can be modified for different data types.
Abstract: I Introduction 1 Introduction II Preparing For a MV Analysis 2 Examining Your Data 3 Factor Analysis III Dependence Techniques 4 Multiple Regression Analysis 5 Multiple Discriminate Analysis and Logistic Regression 6 Multivariate Analysis of Variance 7 Conjoint Analysis IV Interdependence Techniques 8 Cluster Analysis 9 Multidimensional Scaling and Correspondence Analysis V Moving Beyond the Basic Techniques 10 Structural Equation Modeling: Overview 10a Appendix -- SEM 11 CFA: Confirmatory Factor Analysis 11a Appendix -- CFA 12 SEM: Testing A Structural Model 12a Appendix -- SEM APPENDIX A Basic Stats

23,353 citations

Journal ArticleDOI
TL;DR: Relationship marketing, established, developing, and maintaining successful relational exchanges, constitutes a major shift in marketing theory and practice as mentioned in this paper, after conceptualizing relationship relationships as a set of relationships.
Abstract: Relationship marketing—establishing, developing, and maintaining successful relational exchanges—constitutes a major shift in marketing theory and practice. After conceptualizing relationship marke...

19,920 citations

Book
01 Jan 2014
TL;DR: The Second Edition of this practical guide to partial least squares structural equation modeling is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.
Abstract: With applications using SmartPLS (www.smartpls.com)—the primary software used in partial least squares structural equation modeling (PLS-SEM)—this practical guide provides concise instructions on how to use this evolving statistical technique to conduct research and obtain solutions. Featuring the latest research, new examples, and expanded discussions throughout, the Second Edition is designed to be easily understood by those with limited statistical and mathematical training who want to pursue research opportunities in new ways.

13,621 citations


"Influencer Marketing: How Message V..." refers background or methods in this paper

  • ...A collinearity assessment showed no significant levels of collinearity between any sets of predicting variables (with variance inflation factor [VIF] falling between tolerance range .20 and 5.0) (Hair et al. 2014)....

    [...]

  • ...Conversely, PLS-SEM estimates model parameters in a way that maximizes the variance explained in endogenous variables and is preferred for research aimed at theory development and prediction (Hair et al. 2014, p. 14)....

    [...]

  • ...CB-SEM uses a maximum likelihood estimation (MLE) procedure to estimate model coefficients “so that the discrepancy between the estimated and sample covariance matrices is minimized” (Hair et al. 2014, p. 27)....

    [...]

  • ...The latent variables in the current model all have reflective measurements: indicators which predict one particular construct and which are highly correlated to one another and represent the effects of the latent construct (Hair et al. 2014, p. 43)....

    [...]

Posted Content
TL;DR: An evaluation of double-blind reviewed journals through important academic publishing databases revealed that more than 30 academic articles in the domain of international marketing (in a broad sense) used PLS path modeling as means of statistical analysis.
Abstract: Purpose: This paper discusses partial least squares path modeling (PLS), a powerful structural equation modeling technique for research on international marketing. While a significant body of research provides guidance for the use of covariance-based structural equation modeling (CBSEM) in international marketing, there are no subject-specific guidelines for the use of PLS so far.Methodology/approach: A literature review of the use of PLS in international marketing reveals the increasing application of this methodology.Findings: This paper reveals the strengths and weaknesses of PLS in the context of research on international marketing, and provides guidance for multi-group analysis.Originality/value of paper: The paper assists researchers in making well-grounded decisions regarding the application of PLS in certain research situations and provides specific implications for an appropriate application of the methodology.

7,536 citations


"Influencer Marketing: How Message V..." refers methods in this paper

  • ...PLS path modeling is also recommended over CBSEM for testing complex models with many latent variables (Henseler, Ringle, and Sinkovics 2009)....

    [...]

  • ...Then we performed a second bootstrapping analysis, specifying 5,000 subsamples and a 95% significance level, to obtain each path coefficient’s standard error and p value (Henseler, Ringle, and Sinkovics 2009) (Table 3)....

    [...]

Trending Questions (2)
How message value and credibility affect consumer trust of branded content on social media?

The paper states that the informative and entertainment value of influencer-generated posts, along with influencers' credibility components, positively affect followers' trust in influencer-generated branded posts.

When users pay close attention to influencer content, they tend to have greater recall and trust?

Yes, when users pay close attention to influencer content, they are more likely to have greater recall and trust.