PhD Scholarship in Social Media Analytics (2020 Entry)

• Tuition fee
• Monthly stipend (RMB4,500)
• Medical insurance with designate providers
• All above items are covered for up to 36 months based on satisfactory progression
• All regulations set out in the UNNC PGR Scholarship Policy apply

In addition to the above scholarship, successful candidates also have the opportunity to carry out paid teaching (after the completion of Graduate Teaching Assistant (GTA) training) or research assistant duties at UNNC since second year of their PhD programmes.

The above scholarship is to support research projects outlined under the following theme: 

Title of the theme: Social Media as Sources of Innovation Management

Research Background

In the age of Web 2.0, social media websites such as Facebook and Twitter have provided open and free environments for customers to express and publish their thoughts and opinions regarding products and services. These virtual customer communities generate a vast amount of data, which, if extracted and analysed properly, can provide rare and valuable knowledge for product and service innovation. Therefore, social media can serve as new innovation intermediaries for companies to capture the “cognitive surplus” generated outside of organizational boundaries and to integrate external resources and ideas across the entire product innovation and production funnel, spanning ideation, R&D, manufacturing and commercialization. Peer production and the participation of customers in the product design and engineering are transforming traditional business models and driving the competitiveness of companies.

This project focuses on examining various innovation models to monetize and extract value from crowd-generated content on social media. The insights from this research can contribute to the understanding of social media as a social-technological phenomenon, and, most importantly, to the understanding of how social media is utilized by organizations to manage innovation and new product development. A mixed method approach will be developed by combining natural language processing techniques, imagine processing algorithms, and predictive modelling to solve the previous methodological limitations in quantifying social media factors and addressing the subjectivity of social media data.

Admissions requirements for the programme in addition to the general scholarship requirement, if any:

It is expected that qualified applicants are familiar with, or are equipped with basic coding skills to develop, the following data mining/machine learning skills which include but are not limited to:

• Natural language processing, e.g., text mining and sentiment analysis
• Image processing techniques, e.g., Oriented FAST and Rotated BRIEF algorithms
• Predictive modelling and data analytics
• Network analysis 

Informal inquiries may be addressed to Prof. Patrick Chau (Patrick.Chau@nottingham.edu.cn) or Dr. Jenny PU (jenny.pu@nottingham.edu.cn), but formal applications should follow the instructions in ‘How to apply’ section. Please specify 2003ERA_PC as scholarship reference code when submitting application.

PhD programmes at the UNNC are composed of 3 years research and a 1 year thesis pending period for full time PhDs. Full time PhDs are expected to submit their theses within a maximum of four years from initial registration. PhD supervision is undertaken jointly by academics from the University of Nottingham Ningbo China (UNNC) and the University of Nottingham UK (UNUK). On successful completion, students will be awarded the University of Nottingham PhD degree, and no reference will be made on the degree certificate as to where the degree has been completed. The University of Nottingham PhD degree will be accredited by the Chinese Ministry of Education.

Applicants must have a first class honours undergraduate degree or 65% and above for a Masters’ degree from a British university, or the equivalent from other institutions.

Applicants must meet the required English language proficiency for the relevant subject area. IELTS 6.5 (minimum 6.0 in all elements) or its equivalent is required for Faculty of Science and Engineering (FoSE) scholarship applicants.

More details can be found on the ‘entry requirements’ page of the website.

No separate application is required for applying for a scholarship but please make sure you quote the scholarship reference number in your PhD application form. It normally takes 7-8 weeks for a final decision to be made after the closing date. List of required documents can be found on the ‘how to apply’ page.