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Designing a Model for Community Participation

Evolving inDICEs Community Creation

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Maxime: Gallery Media Manager

Avatar: Official proposal Official proposal
16/03/2021 12:09  

What if:

Scenario 4: What if as a (role) researcher I could (action) analyze data in the participatory platform with (Tools/Data/features from the inDICEs observatory) the inDICEs (webLyzard) dashboard so that (outcome/Impact) allow to analyze and compare data from the participatory platform and the external world.

Persona

  • Goals: Increase burstiness, virality, and long term engagement with her gallery’s online audience
  • Background: Media management
  • Pronouns: She/Her
  • Pain points: limited resources and limited interaction with audience in person due to Covid-19, difficulty communicating or creating solutions with ICT professionals unfamiliar with CHIs
  • Needs: Benchmark her gallery’s performance with other CHI’s within the context of the pandemia, resources on digital engagement during Covid-19

User Scenario

Maxime is a media manager who creates a strategy for measuring the impact of digital participation on different online platforms for her gallery. In the course of her research, she aims to access useful and relevant data with the InDICEs dashboard to analyze and compare data from the participatory platform and other social media platforms to see the difference in burstiness, virality, and long term engagement. Maxime’s aim is to create a strategy for execution and impact to best utilize the gallery’s limited resources for increased online presence and reach out her audience while there exists the need for social distancing. She participates in a survey that gathers data on varying experiences and strategies for culture makers and artists in terms of their digital outreach and hopes to gain insights with the published results. 


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AUTOMATED DATA CONTENT ANALYSIS

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Date range:  
Color codes for sentiment analysis: Negative vs Positive
Endorsements count0
Maxime: Gallery Media Manager Comments 0

Reference: IN-PROP-2021-03-97
Version number 4 (of 4) see other versions
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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 870792.
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