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Social and Behavioral Sciences Commons™
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Articles 1 - 3 of 3
Full-Text Articles in Social and Behavioral Sciences
Online Content Consumption: Social Endorsements, Observational Learning And Word-Of-Mouth, Qian Tang, Tingting Song, Liangfei Qiu, Ashish Agarwal
Online Content Consumption: Social Endorsements, Observational Learning And Word-Of-Mouth, Qian Tang, Tingting Song, Liangfei Qiu, Ashish Agarwal
Research Collection School Of Computing and Information Systems
The consumption of online content can occur through observational learning (OL) whereby consumers follow previous consumers’ choices or social endorsement (SE) wherein consumers receive content sharing from their social ties. As users consume content, they also generate post-consumption word-of-mouth (WOM) signals. OL, SE and WOM together shape the diffusion of the content. This study examines the drivers of SE and the effect of SE on content consumption and post-consumption WOM. In particular, we compare SE with OL. Using a random sample of 8,945 new videos posted on YouTube, we collected a multi-platform dataset consisting of data on video consumption and …
Gender And Racial Diversity In Commercial Brands’ Advertising Images On Social Media, Jisun An, Haewoon Kwak
Gender And Racial Diversity In Commercial Brands’ Advertising Images On Social Media, Jisun An, Haewoon Kwak
Research Collection School Of Computing and Information Systems
Gender and racial diversity in the mediated images from the media shape our perception of different demographic groups. In this work, we investigate gender and racial diversity of 85,957 advertising images shared by the 73 top international brands on Instagram and Facebook. We hope that our analyses give guidelines on how to build a fully automated watchdog for gender and racial diversity in online advertisements.
Text Analytics Approach To Examining Corporate Social Responsibility, Nurul Asyikeen Binte Azhar, Gary Pan, Poh Sun Seow, Andrew Koh, Wan Ying Tay
Text Analytics Approach To Examining Corporate Social Responsibility, Nurul Asyikeen Binte Azhar, Gary Pan, Poh Sun Seow, Andrew Koh, Wan Ying Tay
Research Collection School Of Computing and Information Systems
This research article explores a text analyticsapproach to assess the prominence of corporate social responsibility in 554Singapore-listed firms through a content analysis of the news. Instead ofrelying on publications by the firms, third-party news coverage is used toreduce potential biases due to over-reporting. A dataset of news articles onthe included firms published during fiscal years 2015 and 2016 is crawled, andthe articles’ content is parsed to search for information related to corporatesocial responsibility. Graph theory is subsequently used to create acollaborative network of listed firms’ corporate social responsibilityactivities. The results highlight a more automated and scalable means ofassessing the prominence …