TY - GEN
T1 - PersaLog
T2 - 2017 ACM SIGCHI Conference on Human Factors in Computing Systems, CHI 2017
AU - Adar, Eytan
AU - Gearig, Carolyn
AU - Balasubramanian, Ayshwarya
AU - Hullman, Jessica
N1 - Funding Information:
This was supported by the NSF under grant IIS-1421438. We are gratefully to our many respondents for their input.
Publisher Copyright:
© 2017 ACM.
PY - 2017/5/2
Y1 - 2017/5/2
N2 - Content personalization - automatically modifying text and multimedia features within articles based on the reader's individual features - is evolving as a new form of journalism. Informed by constraints articulated through a survey of journalists, we have implemented PersaLog, a novel system for creating personalized content (e.g., text and interactive visualizations). Because crafting, and validating, personalized content can be challenging to scale across articles (unlike feed personalization), we offer a simple Domain Specific Language (DSL), and editing environment, to support this task. Persa-Log is particularly designed to support the personalization of existing text and visualizations. Our work provides guidelines for personalization as well as a system that allows for both subtle and dramatic personalization-driven content changes. We validate PersaLog using case and lab studies.
AB - Content personalization - automatically modifying text and multimedia features within articles based on the reader's individual features - is evolving as a new form of journalism. Informed by constraints articulated through a survey of journalists, we have implemented PersaLog, a novel system for creating personalized content (e.g., text and interactive visualizations). Because crafting, and validating, personalized content can be challenging to scale across articles (unlike feed personalization), we offer a simple Domain Specific Language (DSL), and editing environment, to support this task. Persa-Log is particularly designed to support the personalization of existing text and visualizations. Our work provides guidelines for personalization as well as a system that allows for both subtle and dramatic personalization-driven content changes. We validate PersaLog using case and lab studies.
KW - Guidelines
KW - News personalization
KW - Personalized content
UR - http://www.scopus.com/inward/record.url?scp=85044865060&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85044865060&partnerID=8YFLogxK
U2 - 10.1145/3025453.3025631
DO - 10.1145/3025453.3025631
M3 - Conference contribution
AN - SCOPUS:85044865060
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 3188
EP - 3200
BT - CHI 2017 - Proceedings of the 2017 ACM SIGCHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 6 May 2017 through 11 May 2017
ER -