Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

Spatial and Temporal Analysis of Social Media Response to Live Events: The Milano Fashion Week

1,049 views

Published on

Social media response to catastrophic events, such as natural
disasters or terrorist attacks, has received a lot of attention.
However, social media are also extremely important in the
context of planned events, such as fairs, exhibits, festivals,
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. We consider a
speci fic scenario, the Milano Fashion Week (MFW), which
is an important event in our city.
We focus our attention on the spreading of social content
in space and time, measuring the spreading of the event propagation
in the territory. We build diff erent clusters of fashion brands,
we characterize several features of propagation in space and
we correlate them to the popularity of involved actors. We
show that the clusters along space and popularity dimensions are loosely correlated, and that domain experts are
typically able to understand and identify only popularity
aspects, while they are completely unaware of spatial dynamics of social media response to the events.
Scientific papers related to this research have been published at WWW2017 conference in Perth (within the LocWeb workshop) and at ICWE2017 conference in Rome.

Published in: Data & Analytics
  • Be the first to comment

Spatial and Temporal Analysis of Social Media Response to Live Events: The Milano Fashion Week

  1. 1. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Spatial and Temporal Analysis of Social Media Response to Live Events: The Milano Fashion Week Marco Brambilla, Stefano Ceri, Florian Daniel, Gianmarco Donetti marco.brambilla@polimi.it marcobrambi
  2. 2. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. PopeElection
  3. 3. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. PopeElection Guess what
  4. 4. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. PopeElection Guess what He gets elected anyway
  5. 5. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Concerts?
  6. 6. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Fashion?
  7. 7. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Gente guarda cell in fashion
  8. 8. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Gente guarda cell in fashion
  9. 9. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Research Questions “Are live events still relevant? • Can online visibility be described simply by how famous is the brand? • Does physical participation still matter? • Can we predict how brands behave within events?
  10. 10. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Method • Collection of domain knowledge from field experts • Extraction of social network content • Popularity, space and time analysis of brand impact • Correlation across dimensions • Prediction of category of a brand
  11. 11. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Domain Experts Official calendar Posts Posts Classified by Brand query wrangling Brands& events Data storage Data Acquisition Process
  12. 12. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. The Data In fashion Prominence of Instagram Higher geolocation share
  13. 13. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Spatial Response in Time Analyze the social media response to the events with respect to the geographical location of posting Within the city of the event (Milan) Two types of signals: 1. The official calendar events 2. The geographical positioning and timestamping of posts of social media
  14. 14. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Spatial Response in Time 1 week before the event The week of the event 1 week after the event Blue dots: social media posts Red stars: physical locations of shows [Day by day animation]
  15. 15. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Spatial Response in Time – Grid and Metrics Method: Grid over the city Density of posts in cells Measures: Gini coefficient # of alive, active and strongly active cells Average distance of posts vs. event location
  16. 16. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Gini coefficient The Gini coefficient is a measure of statistical dispersion The Gini coefficient measures the inequality among values of a frequency distribution: Gini coefficient = 0 Perfect equality, where all values are the same (e.g., where every cell has the same number of posts) Gini coefficient = 1 Maximal inequality among values (e.g., where only one cell has all the social media activity, and all others have no posts geo-located inside, the Gini coefficient will be very nearly one).
  17. 17. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Gini coefficient We compute the Gini coefficient: 1. Over the entire grid over the Milano area 2. Over only those cells that results alive for at least one brand in the specific frame of analysis
  18. 18. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Alive, Active and Strong cells Three types of cells: ALIVE: a cell with more than 1% of the total number of posts ACTIVE: a cell with more than 10% of the total number of posts STRONG: a cell with more than 20% of the total number of posts
  19. 19. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Alive, Active and Strong cells And the difference between subsequent frames (e.g. 3h -> 6h) in terms of on/off for each specific type of cell 3 hours 6 hours 2 on 1 off ALIVE cells
  20. 20. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Average distance Compute the average distance of the posts from the events, in terms of cells, for each brand b, in the following way: 1 𝑛°𝑜𝑓𝑃𝑜𝑠𝑡(𝑔𝑟𝑖𝑑) 𝑐𝑒𝑙𝑙∈𝑔𝑟𝑖𝑑 𝑛°𝑜𝑓𝑃𝑜𝑠𝑡 𝑐𝑒𝑙𝑙 ∗ 𝑑𝑖𝑠𝑡𝑎𝑛𝑐𝑒(𝑐𝑒𝑙𝑙, 𝑒𝑣𝑒𝑛𝑡. 𝑐𝑒𝑙𝑙) Using Manhattan distance for the cell grid
  21. 21. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Spatial Response in Time – Slots and Characterization Temporal granularity: 3h, 6h, 24h, whole analysis period
  22. 22. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. All brands – Geo response K-Means clustering result Spatial Response in Time - Clustering Yellow, with low average distance, the most concentrated Red, with average distances slightly higher Green, with the highest results for average distance, the most dispersed Blue, a single element with highest number of alive cells K-means clustering in a PC85-dimensional space
  23. 23. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Response Volume in Time Analyze the social media response to the events with respect to the axis of time Two types of signals: 1. The official calendar events 2. The volume of posts on social media Versace Number of posts: 4358 on Instagram, 389 on Twitter
  24. 24. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Time Response – (pseudo) Causality Study the causality relationship between the events calendar signal and the social media signal through a series of Granger Causality tests Versace Number of posts: 4358 on Instagram, 389 on Twitter Versace Grange Causality tests result
  25. 25. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Time Response – Causality Curves
  26. 26. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Causality Curves Clustering K-means clustering All brands – Granger Causality tests result K-Means clustering – 4 Cluster Centroids
  27. 27. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Clustered Temporal Causality All brands Granger Causality tests result All brands – Granger Causality tests result K-Means clustering – 4 Cluster Centroids Yellow, with high immediate response Red, with response peak delayed at 15 minutes Green, with delayed response peak at 45-60 minutes Blue, with mild initial response and a 3 hours lagged response peak
  28. 28. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Time Response Prediction Prediction model for the cluster membership of a brand based on the Granger tests results given features related to the events and brands
  29. 29. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Time Response Prediction Random Forest: accuracy close to 62%, but only a few “really” wrong. All brands – Granger Causality tests result Ground Truth from K-Means clustering All brands – Granger Causality tests result Predictionof the cluster membership
  30. 30. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. All brands – Popularity response K-Means clustering result Brand Popularity Clustering Features: 1. # Posts on Instagram 2. # Likes on Instagram 3. # Comments on Instagram 4. # Tweets 5. # Likes on Twitter 6. # Retweets K-means clustering
  31. 31. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Cluster comparison Accuracy = 44.6%
  32. 32. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Cluster comparison Accuracy = 41.5%
  33. 33. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Cluster comparison
  34. 34. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Clustering Comparison 5 Principal Components The Confusion Matrix regarding the alignment of Time Response vs . Geo Response
  35. 35. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Comparing the different dimensions A complete and well-defined brand categorization is possible only taking into account all three dimensions: Popularity Space Time Comparison Accuracy Time VS Space 44.6% Time VS Pop 41.5% Space VS Pop 38.6% Time SpacePopularity
  36. 36. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Concluding… A method for comparing popularity, temporal and geographical response to brands during live events Limitations: actual presence of posting users is not granted; time and space of posts may not be aligned (e.g., delayed posts; see design scenario: 70% delayed posts) Future work: deep understanding of content for determining physical presence; data fusion with app, IoT, cell phone network
  37. 37. Brambilla, Ceri, Daniel, Donetti. Spatial and Temporal Analysis of Social Media Response to Live Events. Spatial and Temporal Analysis of Social Media Response to Live Events. The Milano Fashion Week Marco Brambilla @marcobrambi marco.brambilla@polimi.it http://datascience.deib.polimi.it http://home.deib.polimi.it/marcobrambi THANKS! QUESTIONS?

×