MindTrek2011 - ContextCapture: Context-based Awareness Cues in Status Updates
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The document discusses the ContextCapture project, which aims to enhance informal information sharing through context-aware applications that integrate with social media platforms like Facebook and Twitter. It highlights the development of a mobile application that allows users to add structured contextual information to their status updates and presents findings from a user study that evaluated its effectiveness and user perceptions. Key insights include the importance of privacy and the preference for high-level abstractions of context information, such as location and activity, over specific details.
![(Example)
• Creating a message:
“*User-defined message]
Sent from [Location] while [Activity] [Description] [Topic] and
[Applications Activity] with [Friends+.”
• As an example, a status update message generated
with the previous rule could be:
“I think this is the killer app for ubicomp!
Sent from Conference Room 1 at UbiComp 2011, Beijing, China
while listening to an interesting presentation by Dr. Firstname
Lastname and using Notepad with 12 Facebook friends nearby.”](https://image.slidesharecdn.com/46-contextcapturewolink-111010045348-phpapp01/85/MindTrek2011-ContextCapture-Context-based-Awareness-Cues-in-Status-Updates-12-320.jpg)
MindTrek2011 - ContextCapture: Context-based Awareness Cues in Status Updates
- 1. ContextCapture: Exploring the Usage of Context-based Awareness Cues in Informal Information Sharing Ville Antila, Jussi Polet, Minna Isomursu VTT Technical Research Centre, Oulu Ari-Heikki Sarjanoja, Petri Saarinen Nokia Research Centre, Oulu & Tampere
- 2. Background – SmarcoS project • Smarcos creates solutions to allow devices and services to communicate in UI level, exchange context information, user actions, and semantic data • It allows applications to follow the user's actions, predict needs and react appropriately to unexpected actions • Partners from – Netherlands, UK, Finland, Belgium, Czech Rep., Italy and Spain www.smarcos-project.eu
- 3. Outline 1. Introduction 2. Research approach 3. ContextCapture –application 4. User study 5. Findings 6. Discussion 7. Conclusions 8. Lessons learned (application and user study) – Demo @ UbiComp 2011, Beijing
- 4. Introduction • Smartphones are equipped with sensors and communication tools, which can provide a wide range of awareness and presence information
- 5. Introduction • Information from the physical world is increasingly “digitalized” and shared – Photos tagged, presence in IM, location check-ins, sports tracking, informal awareness cues in Facebook and Twitter
- 6. Challenges • Context information is often ambiguous or too low- level to be meaningful (e.g. Raw sensor data, GPS coordinates, or just free text) – Also this information contains a lot of noise • We propose to add (some) structure to the data 1. Provide abstracted, ”story-like” context data to social networks (motivation for the user) 2. Gather structured data about these user-defined abstractions in order to label context data (and eventually learn from these associations to provide better abstractions)
- 7. Research approach • Approach: 1. We developed an experimental mobile application, which allows users to add different types of contextual information to their Facebook status updates in a format of a “story” or a narrative of the situation 2. We developed a semantic database which links the abstract, user-defined context labels to the low-level sensor data 3. Conducted a two-week user trial exploring the meaningfulness of different context types and the usage of different abstraction levels
- 8. ContextCapture (1/6) • Architecture – a mobile application and a server-side application, integrated with Facebook (and Twitter)
- 9. ContextCapture (2/6) • Mobile application – Symbian 5th Edition and onwards (Qt), Android 2.2 and onwards – Presents context abstractions to the user on a selectable list, sorted by relevance
- 10. ContextCapture (3/6) • Context recognition is based on different sensors of activity, such as… – accelerometer, ambient light detector, GPS data, open applications on the device, the device system information and nearby Wifi access points and Bluetooth devices – for example: • based on the accelerometer data, a decision is made whether the user is moving or still by using movement detection algorithms • nearby Facebook friends can be detected using Bluetooth scanning
- 11. ContextCapture (4/6) • Context items used in ContextCapture – Activity – physical activity of the user – Applications – currently open applications – Device – device information, such as the device type – Friends – nearby Facebook friends using ContextCapture – Location – abstrations using GPS, network and Wifi scan data, current street address, cell ID – Surroundings – abstractions of physical surroundings using ambient light detector, weather etc.
- 12. (Example) • Creating a message: “*User-defined message] Sent from [Location] while [Activity] [Description] [Topic] and [Applications Activity] with [Friends+.” • As an example, a status update message generated with the previous rule could be: “I think this is the killer app for ubicomp! Sent from Conference Room 1 at UbiComp 2011, Beijing, China while listening to an interesting presentation by Dr. Firstname Lastname and using Notepad with 12 Facebook friends nearby.”
- 13. ContextCapture (5/6) • “Collective” context is gathered from nearby devices (running ContextCapture) – If lacking, the mobile client can ask nearby devices for additional context information, such as GPS coordinates, address, weather etc. – Bluetooth communication is used with a simple protocol over RFCOMM • Request: CCRAControlProtocol:Client:ClientBluetoothNam e:WTHR:Request • Response: CCRAControlProtocol:Server:ServerBluetoothNam e:WTHR:-3 degrees Celsius,Sunny
- 14. ContextCapture (6/6) • Server-side application (Facebook and Twitter integrated) – Context data is stored on the server in a semantic model (RDF) – Formatted status updates are aggregated to social media (Facebook and Twitter)
- 15. User study • 12 participants used ContextCapture for two weeks using their own mobile phones in their everyday lives Research questions Do users perceive an application supporting manual status RQ1 updates through automatic context recognition and collective context as useful or valuable? What kind of abstraction levels (regarding the semantics) are RQ2 understandable for the user?
- 16. The participants… • …were between 30-46 years, 37.25 years on average, six males and six females • …used their own mobile devices and personal Facebook accounts during the trial • …were experienced Facebook users as 25% of them had used the service 1-2 years and the rest for over two years
- 17. Trial setup The participants… 1. …were emailed a short description of the study – Purpose, a short manual, a link with installation instructions and a link to the initial Web questionnaire 2. …used the application for two (2) weeks – During that time, they could tell their experiences through a Web diary (we asked them to fill in the diary at least five times) 3. …were interviewed at the end of the trial – The interviews were semi-structured, including questions about the users’ expectations, attitudes, privacy and the most pleasing and unpleasing experiences related to the usage – The participants also filled a Web questionnaire about their experiences
- 18. Findings (1/3) • Location was rated as the most useful context field (average: 4.1/5.0) – Status updates with location information were seen most informative as people can use them to also reference their current activities or point out features from the environment 5 = Very useful 5.0 4.1 4.0 3.2 2.8 2.9 3.0 2.4 2.3 2.0 1.0 1 = Not useful at all Locat ion Device Friends Applicat ions Act ivit y Surroundings
- 19. Findings (2/3) • Weather information, which was related to Surroundings field, was also seen highly interesting – The study was done only in Finland, so this might be a “cultural characteristic” • Application and Device were considered as the least useful fields (average: 2.3/5.0 and 2.4/5.0) – It seemed that many participants did not want to “advertise” the device they were using; – Open applications were often unrelated or uninteresting
- 20. Findings (3/3) • The participants were clearly aware of their privacy and had thought about it while using the application – E.g. the participants did not use the addresses of their homes or the kindergarten their children were, even though the audience consisted of Facebook friends – The accurate location of places was too sensitive to be shared, many of the participants stated that the semantic meaning of the place is enough • E.g. stating “I’m at home” is adequate enough for the people the message is meant for – In many participants’ opinion sharing friends’ location without permission is not acceptable, participants preferred to use more abstract words, like “group of friends”, instead of giving the exact names
- 21. Discussion • Context information was seen as interesting and useful addition, but the participants hoped that they could have had even more control of the level of abstraction (or more relevant suggestions) • Also the abstract labels for context information were preferred and used more often, such as “home”, “work”, “kindergarten” • The participants also preferred labels referring to the type activity, place or event (e.g. “at the movie” or “at the botanical garden”)
- 22. Conclusions • The current location, activity and surroundings were the most relevant context types (in this study) • Disclosing the nearby friends or colleagues in the status updates was seen as relevant but problematic due to privacy issues • The context types were seen as most meaningful when the used abstraction level was high – Participants felt that exact information, such as street address or coordinates, conveyed a too matter-of-fact type description – Whereas more abstract descriptions, such as “at the movie theatre” or “at the botanical garden” were seen as more illustrative, interesting and meaningful
- 23. Lessons learned… 1. With applications dealing with privacy sensitive information, the information disclosure and privacy should be fully controlled by the user 2. By giving freedom for users to control the disclosure and abstraction level of contextual information, it creates: – meaningfulness and motivation for the users – and in the same time allows the system to gather a set of user-defined context labels with different abstraction levels (which can be associated with the gathered low-level sensor data)
- 24. Demo @ UbiComp 2011 • ContextCapture was demonstrated at UbiComp 2011 in Beijing, China (demo + poster) • The demo version was deployed Social Media including additional information: – Indoor location using Bluetooth ContextCapture Server Internet beacons (coupled with the conference rooms) User with – Conference program (for suggesting WLAN connection Mobile Phone Bluetooth Bluetooth Beacon ongoing talks) connection
- 25. Demo @ UbiComp 2011
- 26. Demo @ UbiComp 2011 • Lessons learned from the demo • Indoor location using Bluetooth beacons worked well • Done using three Nokia N95 devices placed in the rooms with simple software for configuring and providing the indoor location information (e.g. ”Conference Room 1 at UbiComp 2011, Beijing, China”) • Including specific context information about the event enhanced the meaningfulness of the application (and was actually useful!) • We included items in the conference program (e.g. ”Talk by Patel et al.”)
- 27. Thank you! Questions? Ville Antila, ville.antila@vtt.fi Jussi Polet, jussi.polet@vtt.fi