Polemic tweet - IFIP Interact 2013

PolemicTweet Video Annotation and Analysis

through tagged Tweets

Samuel Huron, Petra Isenberg, Jean Daniel Fekete

06/09/13 IFIP Interact 2013 – Polemic tweet

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Petra Isenberg INRIA @dr_pi

Raphael Velt IRI @raphv

Yves Marie Haussonne IRI @ymh_work

Authors and Contributors

Samuel Huron INRIA - IRI @cybunk

Jean Daniel Fekete INRIA @jdfaviz


At IRI we organize seminars on subjects such as

philosophy, design, and digital cultures. !

SITUATION


05/09/2013

IFIP Interact 2013 – Polemic tweet

Previous process

1. Videotape the seminar

2. Manually annotate and tag

3. Publish the video online and let user annotate

PROBLEM


05/09/2013


Problem

2. Annotating a video manually is boring and time-consuming

1. Browsing a video after a conference is difficult

3. Tagging and structuring annotations are even more boring

Inspiration: Microblogging activities

05/09/2013


Communication devices

Motivation

05/09/2013


3. Provide an easily accessible system from annotation to video analysis.

2. Provide a visual backchannel to incite people to tag their tweets.

1. Engage the audience: crowdsource video annotation and tagging by tweet.

A certain type of tag: Sentiments


Current approaches to extract sentiments

Human analysis

Natural Language Processing

Our need

  Fast   Language agnostic   Accurate   Cheap


Why not ask the tweet autor ?

Cost Benefit

- Fast - Language agnostic - Accurate - Cheap, cost is distributed

- Require user effort - Low recall

DESIGN


Design Goals:


1. To crowdsource conference video tagging with structured sentiment metadata.

2. To engage audiences in the tagging process.

3. To visualize annotations for browsing and analyzing the video.

0. Service Design

1. A special syntax to enhance tweets

4. A video player with a visualization

2. A social protocol to organize the event over time

3. A real time visualization to read and write tweets


1. Syntax properties and description:

Green Agreement ++

Red Disagreement --

Yellow References ==

Blue Questions ??

Tag Semantic Color

  Simple

  Brief

  Neutral   Easy to parse

  Expressive

  Unambiguous

Design Rational

2. Social Protocol


A. Before the talk: Instruct the crowd.

B. During the talk: Crowdsource the video tagging with a backchannel.

C. After the talk: Publish on a web video player.

Instruct the crowd


  The network access policy

  The Twitter hashtag

  The website URL

  The tags

3. Backchannel: Real Time Visualization

4. Metadata Video Player

http://goo.gl/zyJYCZ

DEPLOYMENT


25 to Attendees per event


27 Events

9088 Tweets recorded

300 1012 Unique Twitter users

Deployment

EVALUATION



Questions

1. Is the system sufficiently engaging?

3. What is the impact of presenting tweets and tags on a web video player?

2. Does the visual backchannel incite people to add tags?

Data Collection

05/09/2013


Record tweets sent during the events

Log the user interaction on the web video player

Two web surveys, one for participants, one for organizers

RESULT

IFIP Interact 2013 – Polemic tweet 05/09/2013

Question 1: Is the system sufficiently engaging?


0.2 to 7.94 Tweets per minute

0.12 to 2.13 Tags per minute

40% Tweets using our syntax

35 to 45 % Of all individuals used our syntaxe

05/09/2013


Question 1: Is the system sufficiently engaging?

•  Type of Audience. (size, culture, equipment, incentive, distribution) •  Type of Speaker and Twitter Reaction. •  Type of Content. •  Observance of the PT Protocol.

Influential factors for engagement

Question 2: Does the visual backchannel incite people to add tags?

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05/09/2013


Question 3: What is the impact of presenting tweets and tags on a web video player?

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Visualization User seek activity

?

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TODO: Figures p < 0.1 p < 0.1 p < 0.1

0.1 < p < 0.5 0.1 < p < 0.5 P > 0.1

CONCLUSION


The Evaluation was challenging

05/09/2013


  Deployed in the wild   Long period of time   Design change over time   Real life users   Real life setting

Because

Result!

1.The system engaged the audience to provide data for crowdsourced video tagging.

2. The visual backchannel incited people to tag their tweets and thus provided an annotation structure.

3. The media player augmented with the annotated tweet visualization was considered a significant improvement over traditional video players.

Next steps

05/09/2013


As classroom presentations.

Synchronous web seminar.

Public debates, and social TV.

Possible optimizations:


Shared attention. Tag properties. Scalability, user interface design and system.

Subsequent work:


http://goo.gl/c2iqg0

Bubble-TV: Live Visual Feedback for Social TV Broadcast

Visual Sedimentation: Data stream visualization technique

http://goo.gl/KvllnO

User supplied sentiment in tweets

http://goo.gl/XXVzJb

MORE INFOS: + open source + details

THANKS: To people who used the system and people who fund this work:

Thank you !

Contact : [email protected] http://www.cybunk.com Team : http://www.aviz.fr http://iri.centrepompidou.fr

goo.gl/wKG9Sg

THE END


Survey Result

  96% (25) of respondents attended at least one conference had already used twitter at conferences ( 7% only for reading)

  86% (24) reported familiarity with the PT syntax   21% (6) with the LiveTweet interface   35% (14) with the web video player visualization

timeline.

05/09/2013

WIID: Who Is Interaction Design?

Survey Result

In the survey 14 users reported to know what the Tweet Timeline Visualization is.

05/09/2013

WIID: Who Is Interaction Design?

• 64% (9) of these found that provides useful information • 79% (11) agree or strongly agree that the visualization helps them to browse the video • 86% (12) would recommend PT to a friend.

# to view a part of video with : – many tweets: 57% (8) – positive opinions (++): 29% (4) – negative opinions (–): 43% (6) – questions (??): 21% (3) – references (==): 21% (3)

Cost and benefit of tagging technics


- Time consuming - Cost is proportional - Hight recall (100%)

- Mostly targeted at English - Not “off the shelves” - Precision problem - Cost is proportional

- Language agnostic - Accurate

- Fast

Cost Benefit

Mechanical turk

- Language agnostic - Accurate - Fast - Cheap, cost is distributed

- Engage user - Low recall

Natural Language Processing

Polemic tweet - IFIP Interact 2013

Technology

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