Demo Data from SIGIR 2026 / reviewers in the wild / expert
Phil Stenton
dblp:66/2313
· DBLP profile ↗
7ranked-venue papers
0as first author
0since 2021 · last 2017
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 4Artificial intelligence and machine learning · 3
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Human-computer interaction and pervasive computing
2 papers |
Wearable and physiological sensing · 30% Collaborative and social computing · 26% User interface design and tools · 22% | |
| Artificial intelligence
1 paper |
Information extraction and text analysis · 100% |
Topics — the 4 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing › audience experience
audience engagement |
0.2 | 1 | 2014 | Sensing a live audience · CHI 2014 |
Wearable and physiological sensing › biosignal sensing
electrodermal activity |
0.2 | 1 | 2014 | Sensing a live audience · CHI 2014 |
Wearable and physiological sensing › physiological signal analysis
psychophysiological measures |
0.2 | 1 | 2014 | Sensing a live audience · CHI 2014 |
Natural language and speech › Information extraction and text analysis › discourse analysis
discourse structure |
0.0 | 1 | 1988 | Cues and Control in Expert-Client Dialogues · ACL 1988 |
Methods — techniques the papers use, named apart from their topics
user study · 0.3scenario-based exploration · 0.3probes · 0.3questionnaire · 0.2galvanic skin response · 0.2discourse analysis · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Challenges of using Personal Data to Drive Personalised Electronic Programme GuidesabstractMedia researchers are adopting personalisation in diverse ways to deliver increasingly context-sensitive and customised media experiences. This paper explores user attitudes towards a personalised Electronic Programme Guide which tailors media recommendations based on users' personal data. We used scenario based exploration enabled by the use of probes to convey the functionalities of data-driven personalised EPGs and to facilitate user discussions around its potential use. Users preferred personalised EPGs over current popular EPGs but expressed a significant lack of trust in the personal data collection that drives personalisation. Users appreciated the functionalities afforded by personalisation of media but were apprehensive about the implications of the personal data being collected about them, particularly in the context of their homes. This calls for the need to design future personalised media experiences that help enhance trust in these socio-technical settings. Neelima Sailaja, Andy Crabtree, Phil Stenton |
CHI | 3 |
| 2014 | Sensing a live audienceabstractPsychophysiological measurement has the potential to play an important role in audience research. Currently, such research is still in its infancy and it usually involves collecting data in the laboratory, where during each experimental session one individual watches a video recording of a performance. We extend the experimental paradigm by simultaneously measuring Galvanic Skin Response (GSR) of a group of participants during a live performance. GSR data were synchronized with video footage of performers and audience. In conjunction with questionnaire data, this enabled us to identify a strongly correlated main group of participants, describe the nature of their theatre experience and map out a minute-by-minute unfolding of the performance in terms of psycho-physiological engagement. The benefits of our approach are twofold. It provides a robust and accurate mechanism for assessing a performance. Moreover, our infrastructure can enable, in the future, real-time feedback from remote audiences for online performances. Chen Wang 0034, Erik Geelhoed, Phil Stenton, Pablo César |
CHI | 3 |
| 2011 | A research methodology for evaluating location aware experiences
Josephine Reid, Richard Hull 0002, Ben J. C. Clayton, Tom Melamed, Phil Stenton |
Pers. Ubiquitous Comput. | 5 |
| 2010 | Priming, sense-making and help: Analysis of player behaviour in an immersive theatrical experience
Josephine Reid, Richard Hull 0002, Ben J. C. Clayton, Gary Porter, Phil Stenton |
Pervasive Mob. Comput. | 5 |
| 1992 | A Case Study of Natural Language Customisation: The Practical Effects of World Knowledge
Marilyn A. Walker, Andrew L. Nelson, Phil Stenton |
COLING | 3 |
| 1989 | User studies and the design of Natural Language Systems
Steve Whittaker 0001, Phil Stenton |
EACL | 2 |
| 1988 | Cues and Control in Expert-Client DialoguesabstractWe conducted an empirical analysis into the relation between control and discourse structure. We applied control criteria to four dialogues and identified 3 levels of discourse structure. We investigated the mechanism for changing control between these structures and found that utterance type and not cue words predicted shifts of control. Participants used certain types of signals when discourse goals were proceeding successfully but resorted to interruptions when they were not. Steve Whittaker 0001, Phil Stenton |
ACL | 2 |