How should B2B firms create image content for high social media engagement? A multimodal analysis

Abstract

PurposeThis study evaluates the effect of the media image content of business to business (B2B) organizations to accelerate social media engagement. It highlights the importance of strategically designing image content for business marketing strategies.Design/methodology/approachThis study designed a computation extensive research model based upon the stimulus-organism-response (SOR) theory using 39,139 Facebook posts of 125 organizations selected from Fortune 500 firms. Attributes from images and text were estimated using deep learning models. Subsequently, inferential analysis was established with ordinary least squares regression. Further machine learning algorithms, like support vector regression, k-nearest neighbour, decision tree and random forest, are used to analyze the significance and robustness of the proposed model for predicting engagement metrics.FindingsThe results indicate that the social media (SM) image content of B2B firms significantly impacts their social media engagement. The visual and linguistic attributes are extracted from the image using deep learning. The distinctive effect of each feature on social media engagement (SME) is empirically verified in this study.Originality/valueThis research presents practical insights formulated by embedding marketing, advertising, image processing and statistical knowledge of SM analytics. The findings of this study provide evidence for the stimulating effect of image content concerning SME. Based on the theoretical implications of this study, marketing and media content practitioners can enhance the efficacy of SM posts in engaging users.

B2B social media use as a double-edged sword on trust: a social presence theory perspective

“…Organizations have extensively used SM and SNS in particular, to achieve B2B branding, communication, and relationship development (Kamboj et al, 2018;Salo et al, 2018). Firms can perform a wide array of activities on SM, such as posting, forwarding, communication, and gaming (Koponen and Rytsy, 2020;Singh et al, 2023). Existing literature has widely documented the benefits of SM on B2B relationships, such as demonstrating company credibility and benevolence, thus facilitating B2B trust development (Magno and Cassia, 2019;Rose et al, 2021).…”

Analysis and Emotion Recognition of Educational Network New Media Images Based on Deep Learning

“…Although existing research methods have achieved preliminary results in image content analysis and emotion recognition, there are still some shortcomings. Firstly, traditional image content annotation methods often ignore the re-calibration of features when dealing with ENNM images, resulting in inaccurate annotation results [15][16][17][18]. Secondly, in terms of emotion recognition, most existing methods only focus on the judgment of emotion categories, ignoring the recognition of emotion intensity and subtle changes, which fails to meet the high-precision requirements of emotion analysis in educational scenarios [19][20][21].…”