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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

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International World Wide Web Conference, 2010 Session: Visual interfaces

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International world wide web conference 2010 session visual interfaces

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


Presented by Seunghun Ok, IDB



  • Introduction

  • The SSB Prototypes

  • Evaluation

  • Results

  • Discussion & Implications

  • Conclusions

Introduction 1 2

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

Introduction 2 2

Introduction (2/2)

  • The most important concept to consider when designing mobile interfaces is “context”

    • Where an application is used

    • How information is entered and interacted with

  • SocialSearchBrowser (SSB), mobile search prototype

    • 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

The ssb prototype 1 4

The SSB Prototype (1/4)

  • To enhance the search and information discovery experience 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

The ssb prototype 2 4

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 answers

    • SSBmap

      • Represents visually with a map

    • SSBtext

      • Represents as textual addresses arranged in list format

The ssb prototype 3 4

The SSB Prototype (3/4)

  • SSBmap

    • Map-based interface

      • Provides users with a sense of place at a glance

  • SSBtext

    • Text-based interface

The ssb prototype 4 4

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



  • Introduction

  • The SSB Prototypes

  • Evaluation

    • Participants

    • Procedure

    • Resolving Locations via Wizard-of-Oz

  • Results

  • Discussion & Implications

  • Conclusions



  • 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



  • Each participant was required to install the SSBmap and SSBtexton their personal iPhone or iPod Touch device

  • 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 experiences with the two applications

Resolving locations via wizard of oz

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 believe 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 physical latitude/longitude values

    • Mechanical turks means a fake chess-playing machine



  • Introduction

  • The SSB Prototypes

  • Evaluation

  • Results

    • Basic Usage Patterns

    • Experience Samples

    • Content Classification: Queries & Answers

      • Query Classification

      • Answer Classification

    • Location Precision

  • Discussion & Implications

  • Conclusions

Basic usage patterns

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)

Experience samples

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 pinpoint “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

Content classification queries answers

Content Classification: Queries & Answers

Query classification

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

Answer classification

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

Location precision 1 2

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 geographical precision

  • 1. Precise: Locations refer to very specific places

  • 2. Street-level: Locations list a specific street name but no exact 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 Ireland

  • 5. Imprecise: Do not provide the user with any relevant location details

Location precision 2 2

Location Precision (2/2)



  • Introduction

  • The SSB Prototypes

  • Evaluation

  • Results

  • Discussion & Implications

    • Choice of interface

      • Personal Preferences

      • Situational Context

      • Information Need

    • Location precision

    • Hybrid Interface ≠ Text + Map

  • Conclusions

Choice of interface

Choice of interface

  • The choice of user interface depends on three factors

    • Personal preferences

    • Situational context

    • Information need

Personal preferences

Personal Preferences

  • Hypothesis 1 - Gender affects to the choice of user interface

    • 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

Situational context

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

Information need

Information Need

  • The participants’ information need had a strong influence 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

Location precision 1 21

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

Location precision 2 21

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 important from a privacy perspective

    • UI perspective should provide users with more control in specifying 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

Hybrid interface text map

Hybrid Interface ≠ Text + Map

  • The user interface that is solely based on a map visualization is not optimal

  • However, an ideal hybrid solution is not a simple parallel 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 interface modalities. However, the integration of the two modalities in a single hybrid application should involve a mash-up that supports users’ interactions and intentions while on-the-move.



  • The majority of existing mobile location based services 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

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