Dr Weisi Guo, University of Warwick
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Dr. Weisi Guo is an assistant professor at the University of Warwick who runs a research team studying big data, wireless networks, and smart cities. His research focuses on integrating big data analytics into traditional ICT systems to help design solutions for cities. He has received several awards for his work. At Warwick, he is involved with the Warwick Institute for Science of Cities and collaborations with other universities on smart city research through organizations like the Centre for Urban Science and Progress. His research examines how social media data can act as a sensor to understand cities and services by providing high resolution spatial, temporal, and contextual data on issues like sentiment mapping and complex network analysis.
![Why Cities
• Cities are permanent human settlements with a history of almost 10,000 years.
Typical attributes: high population density, specialist economy, public
infrastructure, strong local governance, high import & export volumes.
[Ur City (modern Basra) – 3800 BC]
• Cities occupy 2% of land surface, but account for up to 60-80% of the global
energy consumption.
• In the past decade, first time in history that more than 50% of the world’s
population live in cities. In developed nations, this value is between 70 to 95%.
A third of the most densely populated cities are in the developed world.
[Population density in Paris is comparable to density in Delhi]
• According to the United Nations (2012 Habitat Report), more than 70% of the
world will live in a city by 2050.
• What are the metrics that gauge a city’s performance?](https://image.slidesharecdn.com/drweisigeouniversityofwarwick-160308112833/85/Dr-Weisi-Guo-University-of-Warwick-4-320.jpg)
Dr Weisi Guo, University of Warwick
- 1. Dr Weisi Guo Assistant Professor School of Engineering Warwick Institute for the Science of Cities (WISC) University of Warwick, UK Social Media Data for Planning and Monitoring Services Exchange Assistant Professor Centre for Urban Science and Progress New York University, USA Visiting Professor SCIE Shanghai University, China
- 2. School of Engineering | Warwick Institute for the Science of Cities A bit about me Brief Bio: I graduated with MEng, MA, and PhD degrees in information engineering and computer science from the University of Cambridge. I am currently the joint coordinator in Smart City research theme at the School of Engineering. I have worked in academia and industry for over 7 years. I currently run a research team (3 doctoral and 4 graduate researchers) working at the inter-section of big data, wireless networks and smart cities. I want to design solutions that can integrate big data analytics into traditional ICT systems. Awards in 2014/15: IET Innovation Award 2015: Communications Category Bell Labs Prize Finalist 2014 (only UK recipient) IEEE Best Paper Award 2014 IEEE Communication Society 2014 Best Project 2nd Prize
- 3. Activities at the University of Warwick: WISC & • Warwick is home to the only UK government funded Doctoral Training Centre in Smart Cities (training 50-75 PhD students 2014-2023). The students combine research skills in big data, urban planning, engineering, and social sciences. The centre is called Warwick Institute for Science of Cities (WISC). • Warwick is also part of a global 5 university alliance on smart city research: New York University, Carnegie Mellon, Toronto University, and IIT-Mumbai. The headquarters is called CUSP (Centre for Urban Science & Progress), funded by ex-NYC mayor: Michael Bloomberg. • CUSP is opening its 1st overseas expansion campus in London which sees Warwick and KCL join forces to examine the challenges related to health and big data in cities. • Warwick is also a core partner in the new big data Alan Turing Institute.
- 4. Why Cities • Cities are permanent human settlements with a history of almost 10,000 years. Typical attributes: high population density, specialist economy, public infrastructure, strong local governance, high import & export volumes. [Ur City (modern Basra) – 3800 BC] • Cities occupy 2% of land surface, but account for up to 60-80% of the global energy consumption. • In the past decade, first time in history that more than 50% of the world’s population live in cities. In developed nations, this value is between 70 to 95%. A third of the most densely populated cities are in the developed world. [Population density in Paris is comparable to density in Delhi] • According to the United Nations (2012 Habitat Report), more than 70% of the world will live in a city by 2050. • What are the metrics that gauge a city’s performance?
- 5. Activities at the University of Warwick: HAT • The United Nations has published a set of 5 metrics to gauge the performance of cities: Productivity, Infrastructure, Quality of Life, Equity (Equality), the Environment. • Global rankings of cities use metrics such as: Connectivity, Competitiveness, Power, and Influence. • Quality of Living rankings of cities use metrics such as: Environment, Safety, Public Services and Stability. • Such metrics are seen as complex indicators to the performance of cities in competing for human and material resources. Top Global Cities: New York and London Top Quality of Life Cities: Vienna and Zurich
- 6. Scaling Law of Cities • Cities grow like organisms, and as they grow in size, they also experience more problems and convey more benefits. • The scaling law of problems and benefits is of interest to us, as many of our cities are growing in size, whilst some (i.e., Rust Belt of USA) are shrinking rapidly (20% loss in population in recent years). • Research has shown that whilst mammals experience a sub-linear growth (everything gets less efficient per kg of weight), cities experience super-linear growth (everything gets more per capita).
- 7. Challenges Faced by Cities • Cities face ancient and new challenges, but never has the scale of the problem been so big, and never have we been in a better position to use technology to solve them. • Examples of universal challenges include: pollution (air and water), traffic congestion (inter- and intra- city), crime, energy efficiency, public order, balance between green space and commerce, acoustic noise (highest complaint in NYC), and shocks in temperature (heat is the highest killer in NYC). • What we have to foster is to allow cities to grow in a sustainable and prosperous way (i.e., growth of benefits outweigh problems), otherwise some of our cities may one day be a historical landmark.
- 8. School of Engineering | Warwick Institute for the Science of Cities How can social media data act as a senor and help us understand cities and services? • High Resolution: in the past 5 years, the growing penetration of smartphone usage and social media usage has led to a wealth of data across a wide range of hardware and application orientated research. In particular, social media offers high resolution compared to survey/census approaches: - Spatial Resolution: wireless assisted GPS (~< 10 metres) - Time Resolution: seconds - Scale: Twitter has 316 million users with 500 million messages/day • Detailed Context: Not only is the quantifiable data of interest, but the unstructured text and multimedia data is also of interest. - Text: what are people saying / feeling and how does information spread - Community: how do people connect and follow each other - Habits: what do people do and what behavioural patterns emerge
- 9. School of Engineering | Warwick Institute for the Science of Cities Sentiment Mapping of Services • Sentiment: natural language processing words and phrases into sentiments - Real time mapping of emotions on individual and regional level - Identify areas of sadness and correlate it to real challenges in business and services for targeted prioritised intervention • Case Study of London: converted 600,000 tweets into geo-tagged sentiments - Blue = Sadness - Red = Happiness Unhappiest Wards: Barking, Newham Happiest Wards: Westminster, Hillingdon, Camden
- 10. School of Engineering | Warwick Institute for the Science of Cities Creating Networks from Data • Relationship between Stakeholders: it is important to analyse the relationship between stakeholders, rather than treat them in isolation. • Complex Network: As an example, we model short-ranged trade network across Europe to reveal the following attributes: - Areas of redundancy (benefits: robustness against failure, cons: inefficiency) - Areas of strategic importance / influence or areas of vulnerability - How the network can improve or adapt subject to a constraint or a perceived threat This analysis can be adapted to small-scale networks (within a company) or large-scale multi-level systems (i.e., transport network within a city or country).
- 11. (b) No. of Connecting Links A C B (g) Modularity Class 1 2 3 (c) Average Link Distance D E F (d) Cluster Coefficient F G H I J (a) No. of Critical Links A B School of Engineering | Warwick Institute for the Science of Cities Analysing a Real Trade Network Critical Nodes Importance A Critical & Important Links Connections Influential B Critical & Important Paths Connections C Important Paths Connections Influential F Central Cluster (e) Influence A C (f) Page Rank A C B
- 12. Dr Weisi Guo weisi.guo@warwick.ac.uk School of Engineering Warwick Institute for the Science of Cities (WISC) University of Warwick, UK Thank you for Listening