paper-conference

RMIT at TREC 2021 Fair Ranking Track
This report describes the data, the assumptions, methodology, and our results involved in the participation at the TREC 2021 Fair …
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Where Do Queries Come From?
Where do queries – the words searchers type into a search box – come from? The Information Retrieval community understands …
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Accessing Media Via an Audio-only Communication Channel: A Log Analysis
Studies of interaction log analysis are a common tool to investigate behavioural data and contribute to insights into users’ …
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Accessing Media Via an Audio-only Communication Channel: A Log Analysis
The Meant, the Said, and the Understood: Conversational Argument Search and Cognitive Biases
Many questions of public interest do not have a single answer but come with a set of choices, each of which with its pros and cons.An …
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The Meant, the Said, and the Understood: Conversational Argument Search and Cognitive Biases
Crowdsourcing Backstories for Complex Task-Based Search
Backstories provide vital contextual information for information retrieval evaluation. They are useful as textual representations of …
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Evaluating Fairness in Argument Retrieval
Existing commercial search engines often struggle to represent different perspectives of a search query. Argument retrieval systems …
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Human-in-the-Loop Systems for Truthfulness: A Study of Human and Machine Confidence
Automatically detecting online misinformation at scale is a challenging and interdisciplinary problem. Deciding what is to be …
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RMIT at PAN-CLEF 2020: Profiling Fake News Spreaders on Twitter
Automatic detection of fake news in social media has become a prominent research topic due to its widespread, adverse effect on not …
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Can The Crowd Identify Misinformation Objectively? The Effects of Judgment Scale and Assessor's Background
Truthfulness judgments are a fundamental step in the process of fighting misinformation, as they are crucial to train and evaluate …
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Crowdsourcing Truthfulness: The Impact of Judgment Scale and Assessor Bias
News content can sometimes be misleading and influence users’ decision making processes (e.g., voting decisions). Quantitatively …
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Crowdsourcing Truthfulness: The Impact of Judgment Scale and Assessor Bias