Adding, Retrieving and Browsing Content in Social Media and E-Journalism
type: CreativeWork
description: This thesis explores the use of avatars with facial expressions in social media and e-journalism communication interfaces. This thesis involved three experimental conditions. In the first experimental condition a survey (n=34) and an experiment (n=25) were carried out in order to explore the central problems faced by users during adding and retrieving comments and methods to overcome those problems. The survey intended to find out the position users took towards these metaphors. 25users from the Aljazeera Channel in Doha, Qatar took part. The first experimental condition consisted of two interfaces, TARCS (traditional adding and retrieving comments system) and CMARCS (classification multimodal adding and retrieving comments system). This was carried out in order to assess users' perception of unique text with graphic classification and multimodal in an EARCS (electronic adding and retrieving comments system) interface in the presence and absence of an interactive context. This was implemented in order to assess the role of these unique classification interfaces in a news comment in the term of usability. In the second experiment, forty users evaluated the use of the VARCS (visual adding and retrieving comments system) and MMARCS (multimodal adding and retrieving comments system). Both interfaces evaluated the effect on public opinion as media study and effectiveness, interactivity and user satisfaction in HCI studies. The third experimental condition consisted of one study that investigated the impactbility and usability of facial expressions compared text with graphic and multimodal metaphors. Sixty six users from Al-Arabiya Channel in Dubai, UEA took part in these two experiments. The results obtained show that users had some problems with adding and retrieving comments in social media such as missing data and lack of organisation. Also, the new classification performed better and faster under an interface that implemented avatars with specific facial expressions …
abstract: This thesis explores the use of avatars with facial expressions in social media and e-journalism communication interfaces. This thesis involved three experimental conditions. In the first experimental condition a survey (n=34) and an experiment (n=25) were carried out in order to explore the central problems faced by users during adding and retrieving comments and methods to overcome those problems. The survey intended to find out the position users took towards these metaphors. 25users from the Aljazeera Channel in Doha, Qatar took part. The first experimental condition consisted of two interfaces, TARCS (traditional adding and retrieving comments system) and CMARCS (classification multimodal adding and retrieving comments system). This was carried out in order to assess users' perception of unique text with graphic classification and multimodal in an EARCS (electronic adding and retrieving comments system) interface in the presence and absence of an interactive context. This was implemented in order to assess the role of these unique classification interfaces in a news comment in the term of usability. In the second experiment, forty users evaluated the use of the VARCS (visual adding and retrieving comments system) and MMARCS (multimodal adding and retrieving comments system). Both interfaces evaluated the effect on public opinion as media study and effectiveness, interactivity and user satisfaction in HCI studies. The third experimental condition consisted of one study that investigated the impactbility and usability of facial expressions compared text with graphic and multimodal metaphors. Sixty six users from Al-Arabiya Channel in Dubai, UEA took part in these two experiments. The results obtained show that users had some problems with adding and retrieving comments in social media such as missing data and lack of organisation. Also, the new classification performed better and faster under an interface that implemented avatars with specific facial expressions …
author: Alharbe, Mahmood
keywords: HCI, Multimodal, AVATAR, Comments, Social Media, E-Journalism
license: https://dora.dmu.ac.uk/bitstreams/655da13e-e23b-4840-b90c-6f1bc8728319/download
date published: 2011
date modified: 2026-07-24T06:18:27Z
provider: De Montfort University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: De Montfort University