What Makes a Good and Useful Summary? Incorporating Users in Automatic Summarization Research

TL;DR

This paper investigates how automatic summarization research aligns with user needs, focusing on university students, and proposes a survey methodology to identify gaps and guide future research directions.

Contribution

It introduces a survey approach tailored to different user groups, revealing misalignments between current research and user needs, and suggests new research directions.

Findings

Current summarization research does not fully meet students' needs.

A flexible survey methodology can assess user-specific summarization requirements.

Proposed future research directions aim to improve summary design, development, and evaluation.

Abstract

Automatic text summarization has enjoyed great progress over the years and is used in numerous applications, impacting the lives of many. Despite this development, there is little research that meaningfully investigates how the current research focus in automatic summarization aligns with users' needs. To bridge this gap, we propose a survey methodology that can be used to investigate the needs of users of automatically generated summaries. Importantly, these needs are dependent on the target group. Hence, we design our survey in such a way that it can be easily adjusted to investigate different user groups. In this work we focus on university students, who make extensive use of summaries during their studies. We find that the current research directions of the automatic summarization community do not fully align with students' needs. Motivated by our findings, we present ways to mitigate this mismatch in future research on automatic summarization: we propose research directions that impact the design, the development and the evaluation of automatically generated summaries.