Browsing by Author "Abidi, Faiz"

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    CS5604: Information and Storage Retrieval ​Fall 2016 - CMT (Collection Management Tweets)
    Wagner, Mitchell J.; Abidi, Faiz; Fan, Shuangfei (Virginia Tech, 2016-12-08)
    As the Collection Management Tweets team in the Fall 2016 CS5604 class, we were responsible for processing >1.2 billion tweets, including data transfer, noise reduction, tweet augmentation, and storage via several technologies. Our work was the first step in a pipeline that included many teams and ultimately culminated in a comprehensive information retrieval system. We were also responsible for building a social network (or set of networks) for those tweets, along with their tweeters. In this report, we detail our experience with this project. Additionally, we propose solutions for transferring incremental database updates from MySQL to HDFS and subsequently to HBase, derive a graph structure and relationships from entities identified in tweet collections, and offer a query-independent method for estimating the importance of those entities. We achieve these goals through the use of several open-source software packages, and present open, scalable solutions addressing the objectives we were given.
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    Mapping the Celebrity Endorsement of Branded Food and Beverage Products and Marketing Campaigns in the United States, 1990–2017
    Zhou, Mi; Rajamohan, Srijith; Hedrick, Valisa E.; Rincón-Gallardo Patiño, Sofía; Abidi, Faiz; Polys, Nicholas F.; Kraak, Vivica (MDPI, 2019-10-04)
    Celebrity endorsement used to promote energy-dense and nutrient-poor (EDNP) food and beverage products may contribute to poor dietary habits. This study examined celebrity endorsement of branded food and beverage products and marketing campaigns in the United States (US) from 1990 to 2017. Celebrity endorsement data were collected from peer-reviewed and grey literature. Interactive data visualizations were created for the endorsement relationships between celebrities, companies and products whose nutritional profiles were compared with the US Department of Agriculture’s (USDA’s) Smart Snacks Standards. Logistic regression was used to explore associations between celebrities’ demographic profiles and the nutritional profiles of products. Results showed 542 celebrities were associated with 732 endorsements representing 120 brands of 59 companies across 10 food and beverage categories. Two thirds (67.2%; n = 80) of the brands represented EDNP products that did not align with the USDA’s Smart Snacks Standards. Logistic regression analysis indicated that Millennial (p = 0.008) and male celebrities (p = 0.041) were more likely to endorse EDNP products than Generation Z teen and female celebrities, respectively. No statistical significance was observed for celebrities of other demographic profiles. This study may inform future policies and actions of the US government, industry, researchers and consumer advocacy organizations to use celebrity endorsement to promote healthy food environments for Americans.