Multimodal Post Attentive Profiling for Influencer Marketing

Kim, Seungbae; Jiang, Jyun-Yu; Nakada, Masaki; Han, Jinyoung; Wang, Wei

doi:10.1145/3366423.3380052

Cited by 24 publications

(24 citation statements)

References 15 publications

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“…• Comments produced by political communities tend to be longer, richer in emojis, hashtags and uppercase words, indicating assertive and emotional content than communities around other topics. Kim et al [19] analyzed multiple categories of Influencers (outside politics) finding that such textual features are not very discriminative across the categories. We confirm their findings on our baseline of nonpoliticians, however finding remarkable differences for Influencers on politics.…”

Section: Discussion On Main Findings and Conclusionmentioning

confidence: 99%

“…Considering Instagram, in particular, the literature on user behavior and interactions is reasonably recent and somewhat restricted. Some authors have analyzed user engagement [24,23,19,39] and properties of the textual content shared by Instagram users [40,41], but with no particular focus on political discussions. Closer to our present effort, Zarei et al [22] analyzed user engagement of twelve Instagram profiles, including profiles of politicians, searching for impersonators -i.e., users who simulate others' behavior to perform specific activities, such as spreading fake news.…”

Section: Online Discussion In Social Media Applicationsmentioning

confidence: 99%

“…Understanding how users interact with each other is paramount to uncover how information is disseminated in the platform and how the online debate impacts our society [10,11,7,12,5,13,14]. Prior studies of user behavior on Instagram mainly focused on user engagement based on content type [15,16,17,18,19,20], general characteristics of comments associated with political messages [21,22] and the impact of the posted content on marketing contexts [16,23,24]. The literature lacks an investigation of the networks that emerge from users' interactions, in particular around political contents, networks that play key roles in information dissemination.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

On the dynamics of political discussions on Instagram: A network perspective

Ferreira

Murai

Silva

et al. 2021

Online Social Networks and Media

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Instagram has been increasingly used as a source of information especially among the youth. As a result, political figures now leverage the platform to spread opinions and political agenda. We here analyze online discussions on Instagram, notably in political topics, from a network perspective. Specifically, we investigate the emergence of communities of co-commenters, that is, groups of users who often interact by commenting on the same posts and may be driving the ongoing online discussions. In particular, we are interested in salient co-interactions, i.e., interactions of co-commenters that occur more often than expected by chance and under independent behavior. Unlike casual and accidental co-interactions which normally happen in large volumes, salient co-interactions are key elements driving the online discussions and, ultimately, the information dissemination. We base our study on the analysis of 10 weeks of data centered around major elections in Brazil and Italy, following both politicians and other celebrities. We extract and characterize the communities of co-commenters in terms of topological structure, properties of the discussions carried out by community members, and how some community properties, notably community membership and topics, evolve over time. We show that communities discussing political topics tend to be more engaged in the debate by writing longer comments, using more emojis, hashtags and negative words than in other subjects. Also, communities built around political discussions tend to be more dynamic, although top commenters remain active and preserve community membership over time. Moreover, we observe a great diversity in discussed topics over time: whereas some topics attract attention only momentarily, others, centered around more fundamental political discussions, remain consistently active over time.

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Section: Discussion On Main Findings and Conclusionmentioning

confidence: 99%

Section: Online Discussion In Social Media Applicationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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On the dynamics of political discussions on Instagram: A network perspective

Ferreira

Murai

Silva

et al. 2021

Online Social Networks and Media

View full text Add to dashboard Cite

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“…They concentrate on marketing semantic detection but not on marketing intent inference. An influencer profiling approach is proposed recently to classify influencers with their marketing preference and further classify their posts using multimodal data into several categories [24]. A brand-based post popularity detection model is proposed [25] to predict popularity of multimodal post of specific brand.…”

Section: A Human Intent Analysismentioning

confidence: 99%

Multimodal Marketing Intent Analysis for Effective Targeted Advertising

Zhang

Shen

Zhang

et al. 2022

IEEE Trans. Multimedia

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“…Endorsement is used to be done by celebrities in advertisements such as on TV, on the radio, or in a newspaper. However, the popularity of social media gives a new way to endorse a product which is through social media interaction [6] and the use of influencers [10], [32].…”

Section: Endorsementmentioning

confidence: 99%

Finding the Right Influencers on Instagram for Endorsement Product Using Text Mining

Pamungkas¹,

Yudhianto²,

Sembiring³

et al. 2022

International Journal on Advanced Science, Engineering and Information Technology

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The growth of the Internet has significantly changed our way of life. Social media is being used not only for getting connected with people but also for media sharing, diffusing information, and even marketing. Social media marketing has a significant impact because it can target campaigns appropriately based on the segmentation of the products to be marketed. Furthermore, this approach can provide campaign costs that are less expensive than other traditional methods. One of the methods which are generally used is an endorsement. With the popularity of social media, a new type of endorsement called social media endorsement has been born. This type of endorsement incorporates social media influencers to promote products and goods. However, product and brand owners find it difficult to select suitable influencers to endorse their products. Therefore, we try to solve this problem by creating a recommender system using the clustering method. We collect data from Instagram, one of the most popular social media platforms. The result showed that three clusters produced out of the data had high quality. In addition, we applied Silhouette Coefficient to validate the result, which produced a positive result on .. With such a result, we conclude that this model could be used to categorize which brands or products an influencer normally endorse and recommend product or brand owners if an influencer is suitable based on clustering.

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Multimodal Post Attentive Profiling for Influencer Marketing

Cited by 24 publications

References 15 publications

On the dynamics of political discussions on Instagram: A network perspective

On the dynamics of political discussions on Instagram: A network perspective

Multimodal Marketing Intent Analysis for Effective Targeted Advertising

Finding the Right Influencers on Instagram for Endorsement Product Using Text Mining

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