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Reliability of Human Evaluation for Text Summarization: Lessons Learned and Challenges Ahead

Neslihan Iskender, Tim Polzehl, Sebastian Möller

202111 citations

Abstract

Only a small portion of research papers with human evaluation for text summarization provide information about the participant demographics, task design, and experiment protocol. Additionally, many researchers use human evaluation as gold standard without questioning the reliability or investigating the factors that might affect the reliability of the human evaluation. As a result, there is a lack of best practices for reliable human summarization evaluation grounded by empirical evidence. To investigate human evaluation reliability, we conduct a series of human evaluation experiments, provide an overview of participant demographics, task design, experimental set-up and compare the results from different experiments. Based on our empirical analysis, we provide guidelines to ensure the reliability of expert and non-expert evaluations, and we determine the factors that might affect the reliability of the human evaluation.

Topics & Concepts

Automatic summarizationReliability (semiconductor)Human reliabilityComputer scienceEmpirical researchTask (project management)Set (abstract data type)Affect (linguistics)DemographicsProtocol (science)Data scienceReliability engineeringArtificial intelligencePsychologyHuman errorEngineeringStatisticsMathematicsMedicineSystems engineeringPhysicsSociologyDemographyQuantum mechanicsPathologyPower (physics)Programming languageAlternative medicineCommunicationTopic ModelingNatural Language Processing TechniquesAdvanced Text Analysis Techniques