Conference Agenda (All times are shown in Mountain Daylight Time)

Overview and details of the sessions of this conference. Please select a date or location to show only sessions at that day or location. Please select a single session for detailed view (with abstracts and downloads if available).

 
 
Session Overview
Session
Paper Session 19: Information Seeking and Information Search
Time:
Tuesday, 02/Nov/2021:
11:00am - 12:30pm

Session Chair: Steven Hardin, Indiana State University, USA
Location: Salon B, Lobby Level, Marriott


External Resource:
Presentations
11:00am - 11:30am
ID: 123 / PS-19: 1
Long Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.
Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.
Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/
Topics: Human Computer Interaction (HCI)
Keywords: Information needs, social science, research data, user study

Genuine Information Needs of Social Scientists Looking for Data

Andrea Papenmeier1, Thomas Krämer1, Tanja Friedrich2, Daniel Hienert1, Dagmar Kern1

1GESIS Leibniz Institute for the Social Sciences, Germany; 2German Aerospace Center, Germany

Publishing research data is widely expected to increase its reuse and to inspire new research. In the social sciences, data from surveys, interviews, polls, and statistics are primary resources for research. There is a long tradition to collect and offer research data in data archives and online repositories. Researchers use these systems to identify data relevant to their research. However, especially in data search, users’ complex information needs seem to collide with the capabilities of data search systems. The search capabilities, in turn, depend to a high degree upon the metadata schemes used to describe the data. In this research, we conducted an online survey with 72 social science researchers who expressed their individual information needs for research data like they would do when asking a colleague for help. We analyzed these information needs and attributed their different components to the categories: topic, metadata, and intention. We compared these categories and their content to existing metadata models of research data and the search and filter opportunities offered in existing data search systems. We found a mismatch between what users have as a requirement for their data and what is offered on metadata level and search system possibilities.



11:30am - 12:00pm
ID: 183 / PS-19: 2
Long Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.
Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.
Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/
Topics: Human Computer Interaction (HCI)
Keywords: Conversational Search Systems, Information-seeking Dialogues, Discourse, Spoken Search, Voice-based Personal Assistants

“Can You Search for Me?” Understanding and Improving User-System Dialogues for Complex Search Tasks

Souvick Ghosh

San José State University, USA

Most voice-based personal assistants are suitable for simple tasks which are not conversational but single-turn question-answering. To address this limitation, we investigate the dialogue capabilities of commercial conversational systems and compare them to the standards expected by the users. We designed a set of moderately complex search tasks and used two popular personal assistants to evaluate the user-system interaction. A laboratory-based user study was conducted with twenty-five users and seventy-five search sessions to collect user-system conversational dialogues (for three search tasks). Next, we show that using a set of simple rules, which could be implemented in the immediate future, it is possible to improve the users’ interaction experience and make the system more anthropomorphic. Using a conceptual prototype where a human (Wizard) played the role of the system (unknowing to the users), we demonstrate the efficacy of the guidelines and provide design recommendations for future conversational search systems.



12:00pm - 12:30pm
ID: 258 / PS-19: 3
Long Papers
Confirmation 1: I/we agree if this paper/presentation is accepted, all authors/panelists listed as “presenters” will present during the Annual Meeting and will pay and register at least for the day of the presentation.
Confirmation 2: I/we further agree presenting authors/panelists who have not registered on or before the early bird registration deadline will be removed from the conference program, and their paper will be removed from the Proceedings.
Confirmation 3: I/we acknowledge that all session authors/presenters have read and agree to the ASIS&T Annual Meeting Policies found at https://www.asist.org/am21/submission-types-instructions/
Topics: Human Computer Interaction (HCI)
Keywords: Satisfaction · fMRI · Information Need · Neural Correlates · Search Process.

Neural Correlates of Realisation of Satisfaction in a Successful Search Process

Sakrapee Paisalnan1, Yashar Moshfeghi2, Frank Pollick1

1University of Glasgow, UK; 2University of Strathclyde, UK

In a search process, searchers review documents to gather information relevant to their information need (IN). During this process, searchers may experience the satisfaction of their IN, indicating they have gathered adequate relevant information to answer their need. This complex concept of satisfaction is the ultimate goal of search systems. Most studies in Information Retrieval have been attempted to understand how searchers’ needs are satisfied based on behavioural observation. However, the psychophysiological manifestation during the moment of satisfaction still remains unclear. Here, we use functional Magnetic Resonance (fMRI) to investigate which brain regions are involved during the moment of satisfaction. Twenty-six participants participated in the experiment, designed to represent a search process while being scanned. Our result shows the human brain regions involved during the moment of satisfaction. These findings provide an important step in unravelling the concept of satisfaction in a search process.