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The “Map Trap”? An evaluation of map versus text-based interfaces for location-based mobile search services. International World Wide Web Conference, 2010 Session: Visual interfaces Karen Church, Joachim Neumann, Mauro Cherubini and Nuria Oliver Telefonica Research, Barcelona, Spain - PowerPoint PPT Presentation
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The “Map Trap”? An evaluation of map versus text-based interfaces for location-based mobile search services
International World Wide Web Conference, 2010Session: Visual interfaces
Karen Church, Joachim Neumann, Mauro Cherubini and Nuria OliverTelefonica Research, Barcelona, Spain
2010.7.2Presented by Seunghun Ok, IDB
2
Outline Introduction
The SSB Prototypes
Evaluation
Results
Discussion & Implications
Conclusions
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Introduction (1/2) Users of super-powered mobile handsets tend to use
the Web more heavily than users of simpler devices– Such as iPhone
The world of mobile information access is evolving– Investing mobile version of standard Web services
The interface design of mobile Web services display information– According to which it refers
Geographical
– Based on some order or ranking Time or search engine ranking
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Introduction (2/2) The most important concept to consider when design-
ing mobile interfaces is “context”– Where an application is used– How information is entered and interacted with
SocialSearchBrowser (SSB), mobile search proto-type– SSB gives users the ability to connect with other users while
on-the-go and ask them geo-located questions
The goal of this paper– To analyze the impact that the type of user interface has on
the search and information discovery experience of mobile users
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The SSB Prototype (1/4) To enhance the search and information discovery ex-
perience of mobile users– By pro-actively displaying what other users have been
searching for in a particular location
SSB presents the users with a view of evolving search activities– That is sensitive to their context
Two core interfaces: SSBmap and SSBtext
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The SSB Prototype (2/4) The software architecture consists of two components
– An iPhone application allows users to Issue queries Browse existing queries and their answers Answer other people’s queries
– A server Synchronizes and stores the queries Answers from both application in a common database
Difference between SSBmap and SSBtext
– Representation of user’s location, location of queries and an-swers
– SSBmap
Represents visually with a map
– SSBtext
Represents as textual addresses arranged in list format
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The SSB Prototype (3/4)
SSBmap
– Map-based interface Provides users with a sense of place at a glance
SSBtext
– Text-based interface
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The SSB Prototype (4/4) Two interactive filters
– Time filter Enables selective display of queries based on time
– Query similarity filter Enables users to limit the queries to those that overlap with the
queries that have been previously entered by the user him/herself
Query details– Header
Original query string
– Answers Human generated answers
– Local search results A set of localized search results extracted from Google’s local search
service
– Event search results A set of localized event listings
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Outline Introduction The SSB Prototypes
Evaluation– Participants– Procedure– Resolving Locations via Wizard-of-Oz
Results Discussion & Implications Conclusions
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Participants Participants are required to own an iPhone or iPod
Touch
34 users take part in and complete the live field study– 32 users with an iPhone– 2 users with an iPod Touch– 31 males, 3 females– Ranged in age between 20 and 55 (avg 32.2)
– Lived in various counties in Ireland– Worked in a wide range of employment sectors
Including IT, Accountancy, Banking, Healthcare, Construction, Public
– They used Internet and mobile phone every day
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Procedure
Each participant was required to install the SSBmap and SSBtext on their personal iPhone or iPod Touch de-vice
The live field study ran for a period of 27 days during September 2009
Participants were asked to complete a post-study survey to gather subjective information on their ex-periences with the two applications
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Resolving Locations via Wizard-of-Oz The location is manually resolved using a Wizard-of-
Oz (WoZ) approach– Instead of relying on automatic geo-coding
Would fail in cases like “at the Temple Bar side to the Ha’Penny Bridge”
– Wizard of Oz experiment is a research experiment in which subjects interact with a computer system that subjects be-lieve to be autonomous, but which is actually being operated or partially operated by an unseen human being
Employ 3 mechanical turks – Resolve the textual locations of queries and answers to phys-
ical latitude/longitude values– Mechanical turks means a fake chess-playing machine
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Outline Introduction The SSB Prototypes Evaluation
Results– Basic Usage Patterns– Experience Samples– Content Classification: Queries & Answers
Query Classification Answer Classification
– Location Precision
Discussion & Implications Conclusions
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Basic Usage Patterns The 34 participants generated 1266 interactions in total
– 236 queries, 835 query look-ups, 195 answers
Conducts an independent samples t-test– Participants produce more queries through the map interface than
through the text interface (t[34, 66] = 2.60, p < .05)
– Participants retrieved content more often through the text interface than through the map interface
(t[34, 66] = -3.35, p < .05)
– Participants answered queries more often through the text interface than through the map interface
(t[34, 66] = -1.66, p < .05)
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Experience Samples Collects 94 samples throughout the 1 month period
– 41 via SSBmap and 53 via SSBtext
Samples via SSBmap
– Definite visual and location-specific aspect– Easier mechanism to look at different streets– Better visual overview and works well when attempting to pin-
point “local” queries
Samples via SSBtext
– Accessing a query– Viewing an answer submitted to a query– Seeing if there were any new queries that need to be answered– Quick and easy– Enable a more efficient means of looking up the details of a
query
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Content Classification: Queries & An-swers
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Query Classification 1. General queries: Focus on finding an answer to a particular
question– 1.1 Business / Service– 1.2 Other queries
2. Location explicit queries: Describe a query in which the user’s current location has a definite impact on the information need and the answer expected– 2.1 Addresses / directions– 2.2 Business / services– 2.3 Recommendation / opinion
3. Location implicit queries: Describe needs in which the user is searching for a physical location either directly or indirectly– 3.1 Businesses / services– 3.2 Recommendations
4. Misc queries: All queries that could not be classified into one of the other types
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Answer Classification 1. General Answers: Describe a non location-specific answer
– 1.1 Business / service– 1.2 Recommendation / opinion– 1.3 Other
2. Location explicit answers: Describe an answer that includes an explicit location cue– 2.1 Address / directions– 2.2 Business / service– 2.3 Recommendation / opinion
3. Conversational Answers: Are probes for additional details or statements that appear to be motivated by the desire to chat
4. Application Related
5. Miscellaneous Answers
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Location Precision (1/2) In SSBtext, users can choose to enter a location in free text form
– Manually classified the locations into one of five types based on their geo-graphical precision
1. Precise: Locations refer to very specific places
2. Street-level: Locations list a specific street name but no ex-act street number is provided
3. Neighborhood: Refer to a small area or borough within a city
4. City / county: Refer to a particular city or county within Ire-land
5. Imprecise: Do not provide the user with any relevant loca-tion details
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Location Precision (2/2)
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Outline Introduction The SSB Prototypes Evaluation Results
Discussion & Implications– Choice of interface
Personal Preferences Situational Context Information Need
– Location precision– Hybrid Interface ≠ Text + Map
Conclusions
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Choice of interface The choice of user interface depends on three factors
– Personal preferences– Situational context– Information need
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Personal Preferences Hypothesis 1 - Gender affects to the choice of user in-
terface– Men tend to have better spatial awareness skills than women– Men tend to orientate themselves more easily– The 3 women who took part in our user study indicated that
they preferred SSBtext
But, imbalance in gender exists
Hypothesis 2 – Users’ past experiences with similar applications will also have an impact– Users who preferred SSBmap rated their experiences and
knowledge of mapping services more highly than users who preferred SSBtext
Take-away message 1: Track the application usage/behavior of their users
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Situational Context
Maps are a useful interface when trying to understand one’s surroundings or to visualize a physical area
Take-away message 2: Infer the situational context of the end-user automatically
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Information Need The participants’ information need had a strong influ-
ence on the preferred interface– Participants seeking information related to a specific address
had a strong preference for SSBmap
– Participants preferred SSBtext when answering queries from other users
Take-away message 3: Automatically determining the intent of the user would allow designers to present the most appropriate interface type
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Location precision (1/2)
SSBtext allowed users to specify the location of both queries and answers in more vague terms
Participants were more inclined to choose SSBtext when answering a query
– The effort required to submit an answer and its location via SSBtext was lower than the effort required to accomplish the same task via SSBmap
– We, as human-beings, often do not need exact locations to orientate ourselves and locate items of interest
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Location precision (2/2) High-level location details are probably sufficient in
many circumstances– Such as “around the corner” or “down that street”– Precise locations are not necessarily needed or desired at all
times
Providing support for fuzzy or vague locations is impor-tant from a privacy perspective– UI perspective should provide users with more control in specify-
ing vague or ambiguous locations
Take-away message 4: Mobile search and information access tools should provide support for users to specify fuzzy or vague locations in order to address– Growing privacy concerns of mobile users– Increasing desires for ambiguous locations
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Hybrid Interface ≠ Text + Map The user interface that is solely based on a map vi-
sualization is not optimal
However, an ideal hybrid solution is not a simple par-allel implementation of two interface but rather a smart mix
Take-away message 5: Location-based search tools should support both text-based and map-based inter-face modalities. However, the integration of the two modalities in a single hybrid application should in-volve a mash-up that supports users’ interactions and intentions while on-the-move.
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Conclusions The majority of existing mobile location based ser-
vices are built on top of a map-based visualiztion
The choice of mobile interface depends on a range of factors– Including the user’s personal references, their information
need, their situational context, their need/desire
Hybrid solution that considers each of five take away messages is the way forward in terms of providing useful mobile information access services