A novel social media competitive analytics framework with sentiment benchmarks

He, Wu; Wu, Hao; Yan, Gongjun; Akula, Vasudeva; Shen, Jiancheng

doi:10.1016/j.im.2015.04.006

Cited by 195 publications

(115 citation statements)

References 38 publications

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“…Compressed videos are available online for perceiving and downloading in low quality on the social clouds which decreases the QoE of the user about the social clouds, but these videos will not be recovered in original format in which the video was recorded. Social clouds provide new features of videos hosting and play to attract users to increase the popularity of their organization and generate more revenue [8]. So every social cloud provides customer feedback service to collect user experience about their services but mostly users do not interact with the social service provider and migrate to another social cloud for better QoS.…”

Section: Introductionmentioning

confidence: 99%

Quality of Experience Assessment of Video Quality in Social Clouds

Laghari

Karim

et al. 2017

Wireless Communications and Mobile Computing

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Video sharing on social clouds is popular among the users around the world. High-Definition (HD) videos have big file size so the storing in cloud storage and streaming of videos with high quality from cloud to the client are a big problem for service providers. Social clouds compress the videos to save storage and stream over slow networks to provide quality of service (QoS). Compression of video decreases the quality compared to original video and parameters are changed during the online play as well as after download. Degradation of video quality due to compression decreases the quality of experience (QoE) level of end users. To assess the QoE of video compression, we conducted subjective (QoE) experiments by uploading, sharing, and playing videos from social clouds. Three popular social clouds, Facebook, Tumblr, and Twitter, were selected to upload and play videos online for users. The QoE was recorded by using questionnaire given to users to provide their experience about the video quality they perceive. Results show that Facebook and Twitter compressed HD videos more as compared to other clouds. However, Facebook gives a better quality of compressed videos compared to Twitter. Therefore, users assigned low ratings for Twitter for online video quality compared to Tumblr that provided high-quality online play of videos with less compression.

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Section: Introductionmentioning

confidence: 99%

Quality of Experience Assessment of Video Quality in Social Clouds

Laghari

Karim

et al. 2017

Wireless Communications and Mobile Computing

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“…To process large amounts of user-generated data in social media and extract meaningful knowledge and insights from it, text mining, sentiment analysis and social network analysis have been widely used (He, Wu, Yan, Akula, & Shen, 2015). Text mining can extract meaningful unstructured textual data (He, Zha, & Li, 2013;Hung & Zhang, 2008) and find useful models, trends, patterns, or rules (He, 2011;Romero, Ventura, & García, 2008).…”

Section: Literature Review Big Data and Text Analyticsmentioning

confidence: 99%

Using Big Data and Text Analytics to Understand How Customer Experiences Posted on Yelp.com Impact the Hospitality Industry

Ting

Chen

et al. 2017

CMR

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This study combines programming and data mining to analyze consumer reviews extracted from Yelp.com to deconstruct the hotel guest experience and examine its association with satisfaction ratings. The findings show many important factors in customer reviews that carry varying weights and find the meaningful semantic compositions inside the customer reviews. More importantly, our approach makes it possible to use big data analytics to find different perspectives on variables that might not have been studied in the hospitality literature.

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“…Their findings reveal that there is a need to create a social media data application which will be used for real-time social media CI, marketing intelligence and for identifying specific actionable areas in which businesses are leading or lagging. He et al (2015b) further developed an innovative business-driven social media competitive analytics tool called VOZIQ. Fu et al (2012) proposed a graph-based sentiment crawler which outperformed the methods it was compared with and also proved that sentiment analysis improves web content analysis.…”

Section: Literature Reviewmentioning

confidence: 99%

Competitive analysis of social media data in the banking industry

Afolabi

Ezenwoke

Ayo

2017

IJIMA

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Abstract:Recently, most companies interact more with their customers through the social media, particularly Facebook and Twitter. This has made large amount of textual data freely available on the internet for competitive intelligence analysis, which is helping reposition more and more companies for better profit. In order to carry out competitive intelligence, financial institutions need to take note of and analyse their competitor's social media sites. This paper, therefore, aims to help the banking industry in Nigeria understand how to perform a social media competitive analysis and transform social media data into knowledge, which will form the foundation for decision-making and internet marketing of such institutions. The study describes an in-depth case study which applies text mining to analyse unstructured text content on Facebook and Twitter sites of the five largest and leading financial institutions (banks) in Nigeria: Zenith Bank, First Bank, United Bank for Africa, Access Bank and GTBank. Analysing the social media content of these institutions will increase their competitive advantage and also lead to more profit for the banking institutions in question. The results obtained from this research showed that text mining is able to reveal uncommon and non-trivial trend for competitive advantage from social media data, and also provide specific recommendations to help banks maximise their competitive edge.

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A novel social media competitive analytics framework with sentiment benchmarks

Cited by 195 publications

References 38 publications

Quality of Experience Assessment of Video Quality in Social Clouds

Quality of Experience Assessment of Video Quality in Social Clouds

Using Big Data and Text Analytics to Understand How Customer Experiences Posted on Yelp.com Impact the Hospitality Industry

Competitive analysis of social media data in the banking industry

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