{"id":1441,"date":"2021-04-12T12:30:51","date_gmt":"2021-04-12T09:30:51","guid":{"rendered":"https:\/\/persona.qcri.org\/blog\/?p=1441"},"modified":"2021-04-12T12:34:02","modified_gmt":"2021-04-12T09:34:02","slug":"a-survey-of-15-years-of-data-driven-persona-development","status":"publish","type":"post","link":"https:\/\/persona.qcri.org\/blog\/a-survey-of-15-years-of-data-driven-persona-development\/","title":{"rendered":"A Survey of 15 Years of Data-Driven Persona Development"},"content":{"rendered":"
\"A
A Survey of 15 Years of Data-Driven Persona Development<\/a><\/figcaption><\/figure>\n

Data-driven persona development unifies methodologies for creating robust personas from the behaviors and demographics of user segments. Data-driven personas have gained popularity in human-computer interaction due to digital trends such as personified big data, online analytics, and the evolution of data science algorithms. Even with its increasing popularity, there is a lack of a systematic understanding of the research on the topic.<\/p>\n

To address this gap, we review 77 data-driven persona research articles from 2005\u20132020. The results indicate three periods:<\/p>\n

    \n
  1. Quantification<\/i>\u00a0(2005\u20132008), which consists of the first experiments with data-driven methods,<\/li>\n
  2. Diversification<\/i>\u00a0(2009\u20132014), which involves more pluralistic use of data and algorithms, and<\/li>\n
  3. Digitalization<\/i>\u00a0(2015\u2013present), marked by the abundance of online user data and the rapid development of data science algorithms and software.<\/li>\n<\/ol>\n

    Despite consistent work on data-driven personas, there remain many research gaps concerning<\/p>\n