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Modeling and Analyzing Engagement in Social Network Challenges

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WISE 2016 paper. Published on Springer LNCS 10041. DOI: 10.1007/978-3-319-48740-3_10.

Participation to challenges within social networks is a very effective instrument for promoting a
brand or event. 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.

The full paper has been published at the conference WISE 2016: Web Information Systems Engineering – WISE 2016. pp 140-154. DOI: 10.1007/978-3-319-48740-3_10

In the paper 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
mobilized hundreds of thousands of users on two different social platforms;
our quantitative analysis assesses the validity of the model.

By Politecnico di Milano Data Science Lab.

Published in: Social Media
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Modeling and Analyzing Engagement in Social Network Challenges

  1. 1. Titolo presentazione sottotitolo Milano, XX mese 20XX Modeling and Analyzing Engagement in Social Network Challenges Marco Brambilla, Stefano Ceri, Chiara Leonardi, Andrea Mauri, Riccardo Volonterio Politecnico di Milano, DEIB, Data Science Lab
  2. 2. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Engagement Social Networks are a key aspect to consider when promoting a brand. To measure how effective the communication is, we measure user Engagement.
  3. 3. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Engagement What is Engagement in a Social Network Challenge? • How users are involved in your challenge. • How much they are committed to produce content. • How users will preserve challenge quality • …
  4. 4. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Social Network Challenges – Brand Value Improve community Collect content Visibility
  5. 5. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Social Network Challenges The hard part is to bring users on board! We could use some kind of gamification techniques to keep them engaged. Social network interactions • Appropriate platform • Appropriate challenge
  6. 6. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Gamification The process of game-thinking and game mechanics to engage users and solve problems: • Turning user experience into a game can produce behavior change
  7. 7. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges 5 Elements of Engagement Intrigue • The enterprise needs to develop relevant content to keep users engaged. Reward • Both non-monetary and monetary incentives. • Rewards should match level of difficulty so users gain a sense of accomplishment. Status • Leaderboards codify status in gamification as well as a way to tier users. Community • Social is a key part of gamification: connect, share, and reach out. Challenge • Users must earn a sense of accomplishment to remain engaged. • Challenges will tie back to reward and intrigue over time.
  8. 8. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Non-monetary rewards
  9. 9. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Incentives: Leaderboards Leaderboards frequent motivator: • Newcomers should have hope of reaching top. • Should motivate correct behavior, not just measurable behavior. Whatever is measured, users will optimize for this. [Farmer and Glass, 2010]
  10. 10. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Online challenges Online challenges examples: - Lego Ideas - Starbucks #RaceTogether - NYPD #myNYPD
  11. 11. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges LEGO Ideas • Hard job • Hard competition • Big reward (what?)
  12. 12. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Starbucks “Race together” Spark discussion on racial divide. You never know what you are going to hit.
  13. 13. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges NYPD #myNYPD
  14. 14. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges NYPD #myNYPD NYPD #myNYPD: - Risky - Sensitive - Opposition
  15. 15. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Bottom line Before launching any efforts, run a Possible Negative Outcome Analysis (PNOA) on your idea: • No off-topic messages. • No open-ended input if topic is delicate. • Content filtering before public display.
  16. 16. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Objective We need a model that helps us to identify what actions must we take to keep the challenge engaging for users in order to build value.
  17. 17. Model Actors
  18. 18. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Actors Owner • Initiates the challenge based on some business or marketing need. • High visibility, supports the managers in boosting the social participation.
  19. 19. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Actors Manager • Sets the rules of the game. • Performs activities targeted at enhancing social participation.
  20. 20. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Actors Player • Produce content for the game/challenge. • Obtain visibility. • granted by the community and/or the organizer.
  21. 21. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Actors Fan • Follows the game. • Decides the outcome by voting.
  22. 22. Model Actions / Activities
  23. 23. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Activities / Actions Invite • Spread the challenge. • Augment user base.
  24. 24. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Activities / Actions Appreciate • Share appreciation for • A player • A content published • The whole challenge
  25. 25. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Activities / Actions Award • Grant visibility to a player. • Enforce competition between players.
  26. 26. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Activities / Actions Contribute • Participate to the challenge by • Posting original content • Re-post existing content • Expanding existing content • …
  27. 27. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Actors and activities in Social Network Challenges
  28. 28. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Other aspects Staging • Increase loyalty • Let the user be acquainted to the game mechanics
  29. 29. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Other aspects Timing • Can interfere with • social amplification • the whole challenge • Can boost participation if used wisely
  30. 30. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Other aspects Cross Social Network Fertilization • Same challenge • Multiple Social Network • Can be used to influence behavior indirectly
  31. 31. Firma convenzione Politecnico di Milano e Veneranda Fabbrica del Duomo di Milano Aula Magna – Rettorato Mercoledì 27 maggio 2015 #YourEXPO2015 challenge
  32. 32. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges #YourEXPO2015 challenge
  33. 33. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges #YourEXPO2015 challenge We launched the challenge in a risky situation. • EXPO corruption • No global • … After the PNOA we opted for a themed photo challenge on Instagram.
  34. 34. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges #YourEXPO2015 challenge Weekly challenge • Different themes (hashtags) each week Instagram as the Social Network for content production • Facebook used for cross-fertilization
  35. 35. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Storyboard
  36. 36. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Participation
  37. 37. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Distributions of reactions
  38. 38. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges User clusters
  39. 39. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Conclusion • We defined a model of the actors and activities involved in a social network challenge. • We demonstrated that social platforms are effective in engaging players in games for content generation or enrichment. • We illustrated how the different choices of game organizers impact on the quality and quantity of player’s engagement.
  40. 40. DEIB. Data Science Lab Modeling and Analyzing Engagement in Social Network Challenges Thanks for your time! Questions? Contact: marco.brambilla@polimi.it http://datascience.deib.polimi.it Twitter: @datascience_mi

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