ADM+S Project: Quantifying and Measuring Bias and Engagement

Last updated on Mar 10, 2025
Go to Project Site CACM SIGIR'23 CIKM'23 UbiComp/ISWC'23 SIGIR'24 SIGIR'24 SIGIR-AP'24 ICMI'24 ICMI'24 SIGIR Forum CHIIR'25 MobileHCI'24 ADM+S News and Media Report Technical Report
Damiano Spina
Damiano Spina
Senior Lecturer

I am an academic working in the fields of Information Retrieval and AI, focusing on interactive information retrieval, evaluation of information access systems, and responsible AI.

Publications

SenseSeek Dataset: Multimodal Sensing to Study Information Seeking Behaviors
Information processing tasks involve complex cognitive mechanisms that are shaped by various factors, including individual goals, prior …
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SenseSeek Dataset: Multimodal Sensing to Study Information Seeking Behaviors
Can Users Detect Biases or Factual Errors in Generated Responses in Conversational Information-Seeking?
Information-seeking dialogues span a wide range of questions, from simple factoid to complex queries that require exploring multiple …
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Characterizing Information Seeking Processes with Multiple Physiological Signals
Information access systems are getting complex, and our understanding of user behavior during information seeking processes is mainly …
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Everything We Hear: Towards Tackling Misinformation in Podcasts
Advances in generative AI, the proliferation of large multimodal models (LMMs), and democratized open access to these technologies have …
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Explainability for Transparent Conversational Information-Seeking
The increasing reliance on digital information necessitates advancements in conversational search systems, particularly in terms of …
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Quantifying and Measuring Bias and Engagement in Automated Decision-Making
Navigating online news, media and information has never been more difficult despite the curatorial work of algorithmic news feeds, …
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Towards Detecting and Mitigating Cognitive Bias in Spoken Conversational Search
Spoken Conversational Search (SCS) poses unique challenges in understanding user-system interactions due to the absence of visual cues, …
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Towards Investigating Biases in Spoken Conversational Search
Voice-based systems like Amazon Alexa, Google Assistant, and Apple Siri, along with the growing popularity of OpenAI’s ChatGPT and …
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Walert: Putting Conversational Information Seeking Knowledge into Action by Building and Evaluating a Large Language Model-Powered Chatbot
Creating and deploying customized applications is crucial for operational success and enriching user experiences in the rapidly …
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Human-AI Cooperation to Tackle Misinformation and Polarization
A dominant narrative of the past decade is that algorithms contribute to a misinformed and segregated society. Perhaps paradoxically, …
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AI and Automated Decision-Making in News and Media: Key Technologies and Emerging Challenges
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Designing and Evaluating Presentation Strategies for Fact-Checked Content
With the rapid growth of online misinformation, it is crucial to have reliable fact-checking methods. Recent research on finding …
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Examining the Impact of Uncontrolled Variables on Physiological Signals in User Studies for Information Processing Activities
Physiological signals have the potential to be applied as objective measures to understand the behaviour and engagement of users …
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Towards Detecting Tonic Information Processing Activities with Physiological Data
Characterizing Information Processing Activities (IPAs) such as reading, listening, speaking, and writing, with physiological signals …
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Towards Detecting Tonic Information Processing Activities with Physiological Data
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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