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Extracting and Understanding Call-to-actions of Push-Notifications

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Natural Language Processing and Information Systems (NLDB 2022)


Push-notifications are a communication tool leveraged by many apps to disseminate information, engage with their user base and provide a means of encouraging users to take particular actions. The nuanced intent behind a push is not always distinguishable to the end-user at moments of delivery. This work explores the text content of notifications pushed by a number of prominent apps in the marketplace over the period of 463 days. We present a new ontology that defines notification Call-to-action (CTA) labels in use today. This facilitates greater understanding behind a push and is a step towards standardisation for marketing teams. Subsequently, we then present results of a notification dataset annotated with our CTA labels and propose and evaluate a CTA text classification task, which could facilitate improved solutions for both users subscribed to, and marketers creating, push-notifications.

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    Full app details available on the project website:

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    Crowdsource research platform:

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    Crowdsource annotation platform:

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    Online documentation for this ontology is available at:

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    App categories:

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    Annotated notification examples:

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Funding Acknowledgements

This research has been supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 813497 (PROTECT) as well as with the financial support of Enterprise Ireland, the European Regional Development Fund (ERDF) under Ireland’s European Structural and Investment Funds Programme 2014–2020 and Science Foundation Ireland under Grant Agreement No. 13/RC/2106_P2 at the ADAPT SFI Research Centre at Trinity College Dublin.

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Correspondence to Beatriz Esteves .

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Esteves, B., Fraser, K., Kulkarni, S., Conlan, O., Rodríguez-Doncel, V. (2022). Extracting and Understanding Call-to-actions of Push-Notifications. In: Rosso, P., Basile, V., Martínez, R., Métais, E., Meziane, F. (eds) Natural Language Processing and Information Systems. NLDB 2022. Lecture Notes in Computer Science, vol 13286. Springer, Cham.

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