Analysis of user behaviour and social media content for art and culture events

In our most recent study, we analysed the user behaviour and profile, as well as the textual and visual content posted on social media for art and culture events.

The corresponding paper has been presented at CD-MAKE 2017 in Reggio Calabria on August 31st, 2017.

Nowadays people share everything on online social networks, from daily life stories to the latest local and global news and events. In our paper, we address the specific problem of user behavioural profiling in the context of cultural and artistic events.

We propose a specific analysis pipeline that aims at examining the profile of online users, based on the textual content they published online. The pipeline covers the following aspects: data extraction and enrichment, topic modeling based on LDA, dimensionality reduction, user clustering, prediction of interest, content analysis including profiling of images and subjects.

Picture1We show our approach at work for the monitoring of participation to a large-scale artistic installation that collected more than 1.5 million visitors in just two weeks (namely The Floating Piers, by Christo and Jeanne-Claude). In the paper we report our findings and discuss the pros and cons of the work.

The full paper is published by Springer in the LNCS series in volume 10410, pages 219-236.

The slides used for the presentation are available on SlideShare:

 

Urbanscope: Digital Whispers from the Urban Landscape. TedX Talk Video

Together with the Urbanscope team, we gave a TedX talk on the topics and results of the project here at Politecnico di Milano. The talk was actually given by our junior researchers, as we wanted it to be a choral performance as opposed to the typical one-man show.

The message is that cities are not mere physical and organizational devices only: they are informational landscapes where places are shaped more by the streams of data and less by the traditional physical evidences. We devise tools and analysis for understanding these streams and the phenomena they represent, in order to understand better our cities.

Two layers coexist: a thick and dynamic layer of digital traces – the informational membrane – grows everyday on top of the material layer of the territory, the buildings and the infrastructures. The observation, the analysis and the representation of these two layers combined provides valuable insights on how the city is used and lived.

You can now find the video of the talk on the official TedX YouTube channel:

Urbanscope is a research laboratory where collection, organization, analysis, and visualization of cross domain geo-referenced data are experimented.
The research team is based at Politecnico di Milano and encompasses researchers with competencies in Computing Engineering, Communication and Information Design, Management Engineering, and Mathematics.

The aim of Urbanscope is to systematically produce compelling views on urban systems to foster understanding and decision making. Views are like new lenses of a macroscope: they are designed to support the recognition of specific patterns thus enabling new perspectives.

If you enjoyed the show, you can explore our beta application at:

http://www.urbanscope.polimi.it

and discover the other data science activities we are conducting at the Data Science Lab of Politecnico, DEIB.

 

Extracting Emerging Knowledge from Social Media

Today I presented our full paper titled “Extracting Emerging Knowledge from Social Media” at the WWW 2017 conference.

The work is based on a rather obvious assumption, i.e., that knowledge in the world continuously evolves, and ontologies are largely incomplete for what concerns low-frequency data, belonging to the so-called long tail.

Socially produced content is an excellent source for discovering emerging knowledge: it is huge, and immediately reflects the relevant changes which hide emerging entities.

In the paper we propose a method and a tool for discovering emerging entities by extracting them from social media.

Once instrumented by experts through very simple initialization, the method is capable of finding emerging entities; we propose a mixed syntactic + semantic method. The method uses seeds, i.e. prototypes of emerging entities provided by experts, for generating candidates; then, it associates candidates to feature vectors, built by using terms occurring in their social content, and then ranks the candidates by using their distance from the centroid of seeds, returning the top candidates as result.

The method can be continuously or periodically iterated, using the results as new seeds.

The PDF of the full paper presented at WWW 2017 is available online (open access with Creative Common license).

You can also check out the slides of my presentation on Slideshare.

A demo version of the tool is available online for free use, thanks also to our partners Dandelion and Microsoft Azure.

You can TRY THE TOOL NOW if you want.

Social Media Behaviour during Live Events: the Milano Fashion Week #MFW case

Social media are getting more and more  important in the context of live events, such as fairs, exhibits, festivals, concerts, and so on,  as they play an essential role in communicating them to  fans, interest groups, and the general population. These kinds of events are geo-localized within a city or territory and are scheduled within a public calendar.

Together with the people in the Fashion in Process group of Politecnico di Milano, we studied the impact on social media of a specific scenario, the Milano Fashion Week (MFW), which is an important event in Milano for the whole fashion business.

We presented this work at the Location and the Web workshop co-located with the WWW 2017 Conference in Perth, Australia.

We focus our attention on the spreading of social content  in space, measuring the spreading of the event propagation in space. We build different clusters of fashion brands, we characterize several features of propagation in space and we correlate them to the popularity of the brand and temporal propagation.

We show that the clusters along space, time and popularity dimensions are loosely correlated, and therefore trying to  understand the dynamics of the events only based on popularity  aspects would not be appropriate.

The paper PDF is available as open access PDF online on the WWW 2017 Conference web site. You can download it here.

A subsequent paper on the temporal analysis of the same event “Temporal Analysis of Social Media Response to Live Events: The Milano Fashion Week”, focusing on Granger Causality and other measures, has been published at ICWE 2017 and is available in the proceedings by Springer.

The PowerPoint presentation is available on SlideShare.

Data Science for Good City Life

On March 10, 2017 we hosted a seminar by Daniele Quercia in the Como Campus of Politecnico di Milano, on the topic:

Good City Life

daniele-quercia-good-city-life-smartcity
Daniele Quercia

Daniele Quercia leads the Social Dynamics group at Bell Labs in Cambridge
(UK)
. He has been named one of Fortune magazine’s 2014 Data All-Stars, and spoke about “happy maps” at TED.  His research has been focusing in the area of urban informatics and received best paper awards from Ubicomp 2014 and from ICWSM 2015, and an honourable mention from ICWSM 2013. He was Research Scientist at Yahoo Labs, a Horizon senior researcher at the University of Cambridge, and Postdoctoral Associate at the department of Urban Studies and Planning at MIT. He received his PhD from UC London. His thesis was sponsored by Microsoft Research and was nominated for BCS Best British PhD dissertation in Computer Science.

His presentation will contrast the corporate smart-city rhetoric about efficiency, predictability, and security with a different perspective on the cities, which I think is very inspiring and visionary.

“You’ll get to work on time; no queue when you go shopping, and you are safe because of CCTV cameras around you”. Well, all these things make a city acceptable, but they don’t make a city great.

This slideshow requires JavaScript.

Daniele is launching goodcitylife.org – a global group of like-minded people who are passionate about building technologies whose focus is not necessarily to create a smart city but to give a good life to city dwellers. The future of the city is, first and foremost, about people, and those people are increasingly networked. We will see how a creative use of network-generated data can tackle hitherto unanswered research questions. Can we rethink existing mapping tools [happy-maps]? Is it possible to capture smellscapes of entire cities and celebrate good odors [smelly-maps]? And soundscapes [chatty-maps]?

The complete video of the seminar has been streamed live on youtube and is now available online at https://www.youtube.com/watch?v=Z0IprrZ7phc&w=560&h=315 and embedded here:

The seminar was open to the public and hosted at the Polo Regionale di Como headquarters of Politecnico di Milano, located in Via Anzani 42, III floor, Como.

You can also download the Good City Life flyer.

When a Smart City gets Personal

When people talk about smart cities, the tendency is to think about them in a technology-oriented or sociology-oriented manner.

However, smart cities are the places where we leave and work everyday now.

Here is a very broad perspective (in Italian) about the experience of big data analysis and smart city instrumentation for the town of Como, in Italy: an experience on how phone calls, mobility data, social media, people counters can contribute to take and evaluate decisions.

skype-2

You can read it on my Medium channel.

View story at Medium.com

Modeling and Analyzing Engagement in Social Network Challenges

Within a completely new line of research, we are exploring the power of modeling for human behaviour analysis, especially within social networks and/or in occasion of large scale live events. Participation to challenges within social networks is a very effective instrument for promoting a brand or event and therefore it is regarded as an excellent marketing tool.
Our first reasearch has been published in November 2016 at WISE Conference, covering the analysis of user engagement within social network challenges.
In this paper, we take the challenge organizer’s perspective, and we study how to raise the
engagement of players in challenges where the players are stimulated to
create and evaluate content, thereby indirectly raising the awareness about the brand or event itself. Slides are available on slideshare:

We illustrate a comprehensive model of the actions and strategies that can be exploited for progressively boosting the social engagement during the challenge evolution. The model studies the organizer-driven management of interactions among players, and evaluates
the effectiveness of each action in light of several other factors (time, repetition, third party actions, interplay between different social networks, and so on).
We evaluate the model through a set of experiment upon a real case, the YourExpo2015 challenge. Overall, our experiments lasted 9 weeks and engaged around 800,000  users on two different social platforms; our quantitative analysis assesses the validity of the model.

cross-platform_pdf

 

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CityOmeters, our solution for smartcity analysis and management, presented at EXPO2015

CityOmeters, the complete solution proposed by Fluxedo for smart city management that includes social engagement via micro-planning and big data flow analytics over social content and IoT, has been presented today at EXPO 2015 in Milano, in the Samsung and TIM pavilion.
See the slides below:

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My interview on Social Media and Society: what I said (and what I didn’t)

My recent interview on the evolution of social media and its role in modern society is available on YouTube (in Italian only, sorry about that).

While the 3+ minutes of speech necessarily had to be a general overview on the role and recent changes of social media, I wish to summarise here the some technical aspects of it.

As I mentioned in the presentation:

  • social media changed a lot since their early days, from being consumed on PCs to mobile devices, from general purpose social networks connecting friends to digital stages where we “sell” our life to the entire world, from places where to share personal information to platforms where to publish also objective information coming from the real world experience.
  • social media are nowadays a valuable source of information for companies, who look for (and find) their customers through social media marketing and advertising, and public institutions and researchers, that can leverage on a large amount of data for providing benefits to our everyday life
YourExpo2015 - the Instagram Photo Challenge of Expo2015 MilanoWhat I didn’t say is how you can do that. Well, it’s pretty simple.
The ingredients of the recipe:
  • A lot of users sharing their profile
  • A lot of content (photos, statuses, geotags, descriptions) shared by people
  • (which makes up a VERY big data problem)
  • crawlers capturing this (or stream capturing systems) and storage as needed
  • MODELS of the context, the problem and the solution
  • and DATA ANALYSIS TOOLS for studying the data and extracting meaningful information
To me, the most valuable points are MODELS and ANALYSIS TOOLS. We are doing a lot of experiments on mixing model-driven techniques with semantic analysis, NLP, and social media monitoring. One example of our experiments is the YourExpo2015 Instagram Photo Challenge.
Have a look and participate if you like. More on this coming soon!

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Community-based Crowdsourcing – Our paper at WWW2014 SOCM

Today Andrea Mauri presented our paper “Community-based Crowdsourcing” at the SOCM Workshop co-located with the WWW 2014 conference.

SOCM is the 2nd International Workshop on the Theory and Practice of Social Machines and is an interesting venue for discussing instrumentation, tooling, and software system aspects of online social network. The full program of the event is here.

Our paper is focused on community-based crowdsourcing applications, i.e. the ability of spawning crowdsourcing tasks upon multiple communities of performers, thus leveraging the peculiar characteristics and capabilities of the community members.
We show that dynamic adaptation of crowdsourcing campaigns to community behaviour is particularly relevant. We demonstrate that this approach can be very e ffective for obtaining answers from communities, with very di fferent size, precision, delay and cost, by exploiting the social networking relations and the features of the crowdsourcing task. We show the approach at work within the CrowdSearcher platform, which allows con figuring and dynamically adapting crowdsourcing campaigns tailored to different communities. We report on an experiment demonstrating the eff ectiveness of the approach.

The figure below shows a declarative reactive rule that dynamically adapts the crowdsourcing campaign by moving the task executions from a community of workers to another, when the average quality score of the community is below some threshold.

The slides of the presentation are available on Slideshare. If you want to know more or see some demos, please visit:

http://crowdsearcher.search-computing.org

 

The full paper will be available on the ACM Digital Library shortly.

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