Team / Department: / Analytics
Address: / Old Street, London
Provisional title for project:
Miningsocial media for insight on luxury automotives
Short abstract of what the project would probably entail, and the data to be used:
This project will require the student to generate useful information from a wide range of social media data to detect trends relating to luxury cars. Social data are valuable resources for marketing and the retail industry. However, as primarily textual data, they are inherently difficult to interpret efficiently. Moreover, it is also difficult to sieve through the noise which are paramount to all social media datasets. Therefore, this study will explore new techniques in text mining to harvest useful information from a large sum of social data from various sources. In particular, it will focus on luxury car brands in order to support the insight capabilities of Spark44. The student will then have the possibility of using the modelled data to tell stories about trends which may be occurring (i.e. responsiveness to marketing campaigns, feedback on new car models, etc.). For this study, Spark44 will provide the student with access to Brandwatch, which provides a means of acquiring a large volume of social media data (including Twitter, Facebook public posts, YouTube, Instagram blogs and forums) which mention automotive themes.
Essential and desirable skills that the student would need to have:
Essentialskills (NB):
-Text mining, language processing and theme / topic classification
-Getting and cleaning data at a large scale
-Able to summarise and present results using data visualisation
Desirable:
-Capable user of R and RStudio.
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Preferred degree programmes (if any):
Would any work by the studentneed to be carried outon site at the Company with the exception of supervisory meetings?
No
Any issues of data confidentiality and IPR that would need to be resolved?
Any conversations relating to Spark44, Jaguar Land Rover or Brandwatch company strategies and / or intended usage of the insights gained should be vetted by each company prior to inclusion in the dissertation.
Preferred selection method
Face to face interview
Support and training offered by the company
Initial briefing meeting with Spark44 global analytics team, global social media directors and possibly representatives from Brandwatch.
Weekly review meetings in person or by telephone can be arranged according to the candidate’s preference.
In addition to the training support offered by Brandwatch (details below), Spark44 will provide ad-hoc training support for any questions the student has relating to usage of Brandwatch and / or clarification of the brief.
In the first 3 weeks of the project, it is recommended that the candidate and Spark44 / Brandwatch teams meet in person every week to ensure the brief is fully understood and the project approach is agreed.
Provided that meaningful results are obtained, Spark44 and Brandwatch intend to partner with the successful candidate to publish a case study of the results.
Should the student be proficient with R, Spark44 will provide an R package which facilitates access to the Brandwatch API for convenient sourcing of data. Spark44 can also provide an instance of RStudio server hosted on Google Cloud Platform for the student. This should enable faster read / write of data from Brandwatch.
Brandwatch will offer:
- Enrolment for the candidate on ourBrandwatch for Studentsprogram. This includes:
- Free access to our flagship product, Brandwatch Analytics for 3 months (data cap applies).
- Online video training program, where you'll learn why social data and intelligence is important, how to use it for research and analysis and how it can be used for future employment.
- Become ‘Brandwatch Qualified’ and embed your qualification badge on your LinkedIn, Twitter, Facebook, blog and CV.
- Receive a personalized certificate and badge.
- Day at Brandwatch HQ in Brighton, meet the teams & get a glimpse behind the scenes of the world’s leading social intelligence company.
- Complementary ticket to the annual Now You Know event in London (Oct 3rd 2018)
Financial assistance offered by the company
I agree to pay the student £500 (plus travel expenses) …
For details on how to apply, please visit: