{"id":{"repo_id":"exeter","oai_identifier":"oai:figshare.com:article/32900615"},"canonical_url":"https://search.dev.ndltd.org/etd/exeter/oai:figshare.com:article/32900615","repository":{"repo_id":"exeter","name":"University of Exeter","base_url":"https://api.figshare.com/v2/oai"},"display":{"title":"WE-MOVEO Audience Innovation and the Democratization of Data","abstract":"This thesis investigates how audience data can be reimagined as an ethical, interpretable, and creator-centred resource for independent filmmaking within the contemporary platform economy. While commercial streaming platforms generate extensive behavioural analytics to optimise engagement and retention, independent filmmakers remain largely excluded from meaningful access to audience evidence that can inform creative practice, distribution, and audience development. Existing data infrastructures are predominantly proprietary, opaque, and designed to serve platform interests rather than the interpretive needs of creators. In response, this research introduces Moveo, a practice-led prototype streaming platform that captures lightweight, consent-based audience feedback through moment-level emoji reactions, post-view reflections, and summary ratings. Rather than pursuing predictive or large-scale behavioural modelling, Moveo adopts a small-data methodology that prioritises transparency, interpretability, and ethical governance. Audience responses are transformed into creator-legible visualisations and narrative reports intended to support creative reflection rather than algorithmic optimisation. Methodologically, the study adopts a practice-led, mixed-methods approach situated at the intersection of design research, critical data studies, human-computer interaction, and film studies. The Moveo platform functions simultaneously as both research artefact and investigative method, enabling theoretical concepts concerning platformisation, participatory media, data ethics, and interpretability to be operationalised through iterative design. Formative evaluation protocols and pilot deployment strategies were developed to examine how ethically generated audience evidence may contribute to editing, curation, funding, and distribution decisions within independent short-film practice.<p></p>","abstract_html":"This thesis investigates how audience data can be reimagined as an ethical, interpretable, and creator-centred resource for independent filmmaking within the contemporary platform economy. While commercial streaming platforms generate extensive behavioural analytics to optimise engagement and retention, independent filmmakers remain largely excluded from meaningful access to audience evidence that can inform creative practice, distribution, and audience development. Existing data infrastructures are predominantly proprietary, opaque, and designed to serve platform interests rather than the interpretive needs of creators. In response, this research introduces Moveo, a practice-led prototype streaming platform that captures lightweight, consent-based audience feedback through moment-level emoji reactions, post-view reflections, and summary ratings. Rather than pursuing predictive or large-scale behavioural modelling, Moveo adopts a small-data methodology that prioritises transparency, interpretability, and ethical governance. Audience responses are transformed into creator-legible visualisations and narrative reports intended to support creative reflection rather than algorithmic optimisation. Methodologically, the study adopts a practice-led, mixed-methods approach situated at the intersection of design research, critical data studies, human-computer interaction, and film studies. The Moveo platform functions simultaneously as both research artefact and investigative method, enabling theoretical concepts concerning platformisation, participatory media, data ethics, and interpretability to be operationalised through iterative design. Formative evaluation protocols and pilot deployment strategies were developed to examine how ethically generated audience evidence may contribute to editing, curation, funding, and distribution decisions within independent short-film practice.&lt;p&gt;&lt;/p&gt;","abstract_has_math":false,"creators":["Emily Skoggard (21039953)"],"institution":null,"degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2026,"date_issued":"2026-06-08T00:00:00Z","date_published":"2026-06-08T00:00:00Z","updated_at":"2026-07-27T19:32:16Z","subjects":["Uncategorised value"],"languages":[],"rights":["All rights reserved","Open Access after 2027-06-15"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["10779/exe.32900615.v1"],"render_values":[{"text":"10779/exe.32900615.v1","href":null,"code":true}]}]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Emily Skoggard (21039953)"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2026-06-08T00:00:00Z"]},{"key":"dc:relation","label":"Dc Relation","values":["https://figshare.com/articles/thesis/WE-MOVEO_Audience_Innovation_and_the_Democratization_of_Data/32900615"]},{"key":"dc:type","label":"Dc Type","values":["Text","Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Uncategorised value"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["All rights reserved","Open Access after 2027-06-15"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["10779/exe.32900615.v1"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["This thesis investigates how audience data can be reimagined as an ethical, interpretable, and creator-centred resource for independent filmmaking within the contemporary platform economy. 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Audience responses are transformed into creator-legible visualisations and narrative reports intended to support creative reflection rather than algorithmic optimisation. Methodologically, the study adopts a practice-led, mixed-methods approach situated at the intersection of design research, critical data studies, human-computer interaction, and film studies. The Moveo platform functions simultaneously as both research artefact and investigative method, enabling theoretical concepts concerning platformisation, participatory media, data ethics, and interpretability to be operationalised through iterative design. 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Existing data infrastructures are predominantly proprietary, opaque, and designed to serve platform interests rather than the interpretive needs of creators. In response, this research introduces Moveo, a practice-led prototype streaming platform that captures lightweight, consent-based audience feedback through moment-level emoji reactions, post-view reflections, and summary ratings. Rather than pursuing predictive or large-scale behavioural modelling, Moveo adopts a small-data methodology that prioritises transparency, interpretability, and ethical governance. Audience responses are transformed into creator-legible visualisations and narrative reports intended to support creative reflection rather than algorithmic optimisation. Methodologically, the study adopts a practice-led, mixed-methods approach situated at the intersection of design research, critical data studies, human-computer interaction, and film studies. 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