Considering People with Disabilitiesas Überusersfor Eliciting Generalisable Coping Strategieson the WebMarkel Vigo1 & Simo...
CopingThe cognitive and behavioral efforts to managedemands that exceed the resources of a person.Lazarus & Folkman, 1984A...
ProblemWe do not know the coping strategiesemployed on the WebACM Web Science 20132 May 2013 3
Why is this importantIf we are able to automatically detect copingwe can provide the means to overcome thesituationACM Web...
What do we proposeACM Web Science 20132 May 2013Transferring the identified strategies frompopulations who cope more frequ...
Why is it challengingCoping occurs seldomOnce every 75 minutes.Novick et al., 2007112 minutes for sighted users95 for visu...
Why is it costlySignificant amount of observationsin the wild are requiredACM Web Science 20132 May 2013 7
What do we propose:Step 1. Observation &Identification of StrategiesACM Web Science 20132 May 2013 81. Observation
What do we propose:Step 2. Implementation ofalgorithms to detectstrategiesACM Web Science 20132 May 2013 91. Observation 2...
ACM Web Science 20132 May 2013What do we propose:Step 3. Deployment in the wild101. Observation 2. Algorithms 3. Deployment
What do we propose:Step 4. Run user studiesACM Web Science 20132 May 2013 111. Observation 2. Algorithms 3. Deployment 4. ...
What do we propose:Refine algorithmsgo to step 2ACM Web Science 20132 May 2013 121. Observation 2. Algorithms 3. Deploymen...
Case studyStep 1. Observation and analysis• 2 independent studies/datasets generatedfrom ethnographic studies and user tes...
Case studyStep 2. Implementation- Retracing: users retrace the steps in asequence of pages.- Re-checking: fast revisitatio...
Case studyStep 3. Deployment• Algorithms deployed in a Firefox add-onACM Web Science 20132 May 2013 15
Case studyStep 4. User study• 18 sighted participants, 10 days• 126 retraces and 67 rechecks• Tabbed browsing was interfer...
Case studyRefinement; then iterate.Tab browsing breaks the interaction contextre-checking:webpagei  wpj  wpi  wpjACM We...
False positive rate (less is better)ACM Web Science 20132 May 2013study 1 study 20.00.20.40.60.81.0study 1 study 20.00.20....
ConclusionThere is an overlap between the copingstrategies of different populationsACM Web Science 20132 May 2013 19
Follow upACM Web Science 20132 May 2013 20Contact@markelvigo | markel.vigo@manchester.ac.ukPresentation DOIhttp://dx.doi.o...
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Considering People with Disabilities as Überusers for Eliciting Generalisable Coping Strategies on the Web

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When users struggle on the Web they employ extreme adaptations to tackle problematic situations, namely coping strategies. If we are able to automatically detect such situations we can provide the means to bypass or pre-empt them. However, isolating these coping strategies is a challenging task: coping occurs seldom and when it happens, coping is not always overtly manifested. Therefore, in order to identify the coping strategies employed by users in situ longitudinal observations have to be conducted, which are resource intensive. We propose a more economical method that transfers the coping strategies employed by groups of users that cope frequently and overtly, such as people with disabilities, to broader populations. To do so, we first identify the coping strategies employed by people with disabilities; then we code these strategies and convert them into coping detection algorithms that are injected into web pages. Remote longitudinal studies are run with broader populations to measure the detection rate of the algorithms. Based on participants’ feedback we iteratively modify the algorithms to adjust them to the coping strategies users employ. We illustrate this method with a case study that transfers the strategies employed by visually disabled users to able-bodied users. We discover that different populations do not only face the same problems, but also exhibit similar strategies to tackle them.

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  • Considering People with Disabilities as Überusers for Eliciting Generalisable Coping Strategies on the Web

    1. 1. Considering People with Disabilitiesas Überusersfor Eliciting Generalisable Coping Strategieson the WebMarkel Vigo1 & Simon Harper2 University of Manchester (UK)1: @markelvigo2: @sharpicACM Web Science 2013markel.vigo@manchester.ac.uksimon.harper@manchester.ac.ukhttp://dx.doi.org/10.6084/m9.figshare.695072
    2. 2. CopingThe cognitive and behavioral efforts to managedemands that exceed the resources of a person.Lazarus & Folkman, 1984ACM Web Science 20132 May 2013 2
    3. 3. ProblemWe do not know the coping strategiesemployed on the WebACM Web Science 20132 May 2013 3
    4. 4. Why is this importantIf we are able to automatically detect copingwe can provide the means to overcome thesituationACM Web Science 20132 May 2013 4
    5. 5. What do we proposeACM Web Science 20132 May 2013Transferring the identified strategies frompopulations who cope more frequent andovertly to general audiences5
    6. 6. Why is it challengingCoping occurs seldomOnce every 75 minutes.Novick et al., 2007112 minutes for sighted users95 for visually impairedVigo and Harper, 2013ACM Web Science 20132 May 2013 6
    7. 7. Why is it costlySignificant amount of observationsin the wild are requiredACM Web Science 20132 May 2013 7
    8. 8. What do we propose:Step 1. Observation &Identification of StrategiesACM Web Science 20132 May 2013 81. Observation
    9. 9. What do we propose:Step 2. Implementation ofalgorithms to detectstrategiesACM Web Science 20132 May 2013 91. Observation 2. Algorithms
    10. 10. ACM Web Science 20132 May 2013What do we propose:Step 3. Deployment in the wild101. Observation 2. Algorithms 3. Deployment
    11. 11. What do we propose:Step 4. Run user studiesACM Web Science 20132 May 2013 111. Observation 2. Algorithms 3. Deployment 4. User studies
    12. 12. What do we propose:Refine algorithmsgo to step 2ACM Web Science 20132 May 2013 121. Observation 2. Algorithms 3. Deployment 4. User studies
    13. 13. Case studyStep 1. Observation and analysis• 2 independent studies/datasets generatedfrom ethnographic studies and user tests• 24 screen reader and screen magnifierusers• 17 coping strategies were identifiedACM Web Science 20132 May 2013 13
    14. 14. Case studyStep 2. Implementation- Retracing: users retrace the steps in asequence of pages.- Re-checking: fast revisitations.ACM Web Science 20132 May 2013 14
    15. 15. Case studyStep 3. Deployment• Algorithms deployed in a Firefox add-onACM Web Science 20132 May 2013 15
    16. 16. Case studyStep 4. User study• 18 sighted participants, 10 days• 126 retraces and 67 rechecks• Tabbed browsing was interfering• Feedback on false positives:– “I’m browsing across tabs”– “I’m comparing different web pages”– “I’m navigating through different tabs”ACM Web Science 20132 May 2013 16
    17. 17. Case studyRefinement; then iterate.Tab browsing breaks the interaction contextre-checking:webpagei  wpj  wpi  wpjACM Web Science 20132 May 2013 17NON-TABBED NON-TABBED NON-TABBED
    18. 18. False positive rate (less is better)ACM Web Science 20132 May 2013study 1 study 20.00.20.40.60.81.0study 1 study 20.00.20.40.60.81.0Retracing Re-checking18• 2nd study: 20 sighted participants, 10 days• 24 retraces, 16 rechecks
    19. 19. ConclusionThere is an overlap between the copingstrategies of different populationsACM Web Science 20132 May 2013 19
    20. 20. Follow upACM Web Science 20132 May 2013 20Contact@markelvigo | markel.vigo@manchester.ac.ukPresentation DOIhttp://dx.doi.org/10.6084/m9.figshare.695072Source codehttps://bitbucket.org/mvigo/copeDatasetshttp://wel-data.cs.manchester.ac.uk/studies/3

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