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TAMU CSCE 655
Amir Fayazi
Shiue-Mei Huang
Spencer Huang
Dheeban Srinivasan Govindarajan
[TWITTERPEEK - VISUAL EXPLORATION OF
TWITTER SPHERE]
This is the proposal to be developed by Fall 2010 CSCE 655 Team.
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CONTENTS
Contents ........................................................................................................................................................................2
1
Introduction ..........................................................................................................................................................3
2
Conceptual basis ...................................................................................................................................................3
3
Team .....................................................................................................................................................................4
4
Research components ..........................................................................................................................................4
4.1
5
External Interfaces ........................................................................................ Error! Bookmark not defined.
Research benefits..................................................................................................................................................5
5.1
6
External Interfaces .......................................................................................................................................5
Prior work .............................................................................................................................................................5
6.1
External Interfaces ........................................................................................ Error! Bookmark not defined.
7
Project plan ...........................................................................................................................................................7
8
Supplemental meterials ........................................................................................................................................9
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8.1
Amir Fayazi ...................................................................................................................................................9
8.2
Shiue-Mei Huang ..........................................................................................................................................9
8.3
Spencer Huang ...........................................................................................................................................10
8.4
Dheeban srinivasan govindarajAN .............................................................................................................11
References ..........................................................................................................................................................12
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INTRODUCTION
S1: Announce Research Topic – Motivate Excitement – Grab Reader’s attention
The research theme we are addressing in our project is visual exploration of twitter sphere. We feel that this is a
very important detail to be addressed, given the progressively larger attention that social networks such as
Twitter, Facebook, etc are getting. Especially Twitter is not anymore a mere social network; it is fast becoming one
of the most important online Information diffusion medium.
S2 : Explain the importance of the topic – Make the reader care
The two specific details we are addressing in our project are: Firstly, we are providing a visualization of relationship
of a specific user to others based on tweet-similarity, twitter’s location and time. Such visualization will help the
user to find out other users in the twitter sphere, who are closer to him in all the above mentioned aspects and
help him in forming his social network based with similar people. Secondly, we are providing a visualization of the
spread of influence of a user’s tweets. We believe this feature will let the user to visually understand the influence
and total spread of all his tweets. We feel that such a feature is a cool feature, as any user would want personally
want to know about his total influence in the twitter sphere.
S3: Identify most significant prior work and conditions
S4: Identify the gap in the field – What is missing in the prior work that your research will address
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CONCEPTUAL BASIS
S1: Your long term objective for this line of research.
This is just a part of the entire scheme of things regarding twitter in the long term. The other parts include
designing a better ranking mechanism. These entirely improve the overall usability of twitter.
S2: Research contribution of proposal, the primary objective.
Use of a new visualization technique and thus improving the overall presentation of the contents to
the user.
S3: Principal hypothesis: the most important statement of what your research will establish that is
new.
Use of a ‘so & so’ (yet -to - be decided) visualization technique for this twitter domain , thus improving the
user understanding of the data being represented.
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S4: Rationale: how/why is this achievable?
Please pour in your ideas here guys
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TEAM
The team is composed of Amir Fayazi, Shiue-Mei Huang, Spencer Huang, and Dheeban Srinivasan Govindarajan.
Each team member’s specialties is described as the following:
Amir
Shiue-Mei loves to observe people and try to understand their behaviors. She worked in Geographic Information
Society. Its mission was to provide consultancy to the Taipei city government. At there, she had to talk with clients
and understand their needs, and then try to help with their problems. These experiences could help to discover
needs and understand behaviors in this project.
Spencer is an experienced graduate student who has worked in the IT industry for a while. Since he is familiar with
Java EE platform and he has exercised publically available YouTube API in the past, his skill set is best suited for the
development of a project that is related to social network and he can contribute by implementing parts relate to
data retrieving, natural language processing, data modeling, and algorithms.
Dheeban is a computer science graduate student with undergraduate research experience for about 2 years,
working on problems in the area of artificial intelligence. His current interest and work is in the application of
machine learning to information retrieval and Ranking mechanism / visualization for social networks. He is also
proficient in Java programming language. Hence, he can contribute in implementing parts relating visualization and
designing logic to explore various large social graphs.
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RESEARCH COMPONENTS
4.1
RESEARCH COMPONENT – DATA COLLECTION COMPONENT
4.2
RESEARCH COMPONENT – EVALUATION COMPONENT
The conceptualization of TwitterPeak is done on the basis of requirements collected from a group of 6 people in
the age group of 21-25 years of age. Hence, these requirements were analyzed and the user needs were collected.
With this user needs collected from the Needs & Requirement analysis phase, we have planned for the following
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evaluation schedule: First, during each phase of the development of our TwitterPeek, we have planned to check
with the user needs, i.e, whether each module we build are actually addressing the user needs or not. This can be
summed up as our formative evaluation phase.
Then, when the final product is finished, we will be submitting this to our project advisor (which is our submission
of project), in order to make sure that our product has met the expected standard of implementation. This can be
viewed as the summative evaluation for our project.
Apart from these, during the building of the product & the interface, we have planned to get informal feedback
from the same 6 set of people, whom we contacted in our requirement analysis phase to get some quick informal
evaluation about our product. This is our quick & dirty evaluation. Once, our product is completed, we have
planned to test our product on a set of 40 user apart from these 6 people who have actually been involved in quick
& dirty evaluation. We have planned to conduct on an field study type of evaluation, by showing demo of our
product at the people’s house, thus by letting them to try our product at their natural environment, without any
constraints. This constitutes our outsider evaluation. Apart from these, we developers will also be testing our
demo from the user’s perspective and this constitutes our insider evaluation.
The goal of the evaluation is to get feedback regarding the features which we have implemented overall – whether
people liked it or not?, and also to get feedback about the individual components of our system – whether they
found it useful. The third goal is to get feedback which will help us to improve our system in the future days to
come. We have decided to go for – Observation method in an uncontrolled environment through informed
consent of the user. We have also planned to use the ‘think-aloud’ method with our users. The recording
technique we have planned to use is “Taking Notes” of user’s experience and comments. These above details will
serve as our qualitative evaluation. Also, we have planned to supplement this process with a questionnaire of
“Structured Task” & a “Likert Scale” style evaluation sheet at the end of the user testing phase to get the
quantitative feedback from the user.
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RESEARCH BENEFITS
5.1
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EXTERNAL INTERFACES
PRIOR WORK
Vizter
Vister is a visualization system for the user to explore his social network. The view of the network will be presented
to the user in a node-link network layout (i.e like the social network graph view we have seen so far). Vizter uses a
spring – embedding layout (i.e, nodes repel each other beyond some small distance, hence they give this bouncing
effect and looks nice to see). Total interaction is only simple mouse based. The nodes can be dragged to different
location, double clicking on the nodes expand or contract the node – increasing the size and also expanding the
node’s network. Exploration is highlighting links/nodes based on connectivity. Also, view of inter-linking of nodes,
manual explicit zoom by some specific user operation and sometimes implicit zoom operation. Searching users
based on queries, highlights the user by adding an “aura” around the user and increasing the size of the node. The
following figure shows the Linkage view – with zooming, panning and Link highlighting.
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Figure.1: Linkage View
X-ray mode to visualize number of friends, different genders in a community (i.e male and female) and also to find
and resize communities with the users in one’s social network. This is shown in Figure.2, 3 & 4.
Fig1: X-ray view of genders
Fig2: X-ray view of groupd
Fig3: Normal view of clusters
TwitViz
This is a tool to allow the user to explore their social network on twitter based on their interest. It provides only 2
features – one is keyword view i.e, displays relationships between keywords of interest and users tweeting about
them, thus helping in identifying users with similar interest to befriend – this helps the users with initial group
formation especially. Second – it just displaying the reciprocal followers i.e, mutual followers - this helps the user
to know how many of whom he is following is following him back. The same ‘node-link’ layout of ‘vizter’ is used
with the same ‘zooming’ techniques. The following figure.1 Shows the TwitViz interface.
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Figure.1: TwitViz Interface
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PROJECT PLAN
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Figure x: Ghant chart
As the above figure suggested, we have the following deliverables: proposal refinement, lo-fi prototype, user
studies 1 and 2, functional prototype 1, and final presentation & paper. For the proposal refinement, Amir would
discuss contribution and research benefit; Mei would discuss evaluation and scenarios; Spencer would discuss
development plan; Dheebann would discuss abstract and prior work. All members must complete by the time
specified in the figure. For story boards and lo-fi prototype, Dheeban would develop data gathering component,
Amir and Spencer would develop other components for this prototype. Mei would elaborate on the storyboards.
Again, the deadline is listed in the above figure. For User study 1, all members would perform the necessary
evaluation, qualitative analysis, and obtain feedbacks. For Functional prototype 1, Amir and Mei would develop
the visual component; Spencer would develop the evaluation component; and Dheeban would development data
collection component. Deadline has been specified. For User study 2, all members together would develop
corresponding evaluation tasks, collect feedbacks via user studies, and analyze quantitative data. Then for final
paper and presentation, Amir would complete method and evaluation section. Mei would complete design
process. Spencer would complete approach and help on evaluation. Dheeban would develop related work.
Deadline has been scheduled.
From the above figure, user study 1 is dependent on the completion of lo-fi prototype. User study 2 is also
dependent on functional prototype 1.
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8.1
SUPPLEMENTAL METERIALS
AMIR FAYAZI
Dd
8.2
SHIUE-MEI HUANG
Technical skills
Languages: C, C Shell, Fortran, HTML, MapBasic, Matlab, SQL, Visual Basic.
Technical knowledge: Familiar with MS Windows, Fedora Linux.
Experience
Research Assistant
08/2008-02/2010
Taiwan Geographic Information Society
Taipei, Taiwan
Participated in “Promoting GIS Development in Taipei City Government” project. Researches and studies were
performed on the GIS development of Taiwan and the rest of the world in order to provide consultancy to the
Taipei city government.
Software Engineer
08/2005-07/2008
YULON GROUP Sin Etke Technology Corporation
Taipei, Taiwan
Participated in the research and development of in-vehicle navigation system. Leader of a team of four, focusing
on gathering information and producing the “point of interest” part of the map.
Education
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Texas A&M University
09/2010 – continue
College Station, Texas
Enrolled in the department of Computer Science and Engineering, in pursuit of M.S. in Computer Science.
National Central University
08/2002 – 07/2004
Taipei, Taiwan
Graduated with M.S. in Geophysics; specialized in Seismology, Tectonics, and Geoscience Information.
Research Area
Through my academic background and employment experiences, I have a growing interest in scientific
visualization and human-computer interaction. I would like to combine my knowledge in earth science and
computer science to explore methods that are capable of integrating GIS set of tools with Scientific Visualization
software together to create a comprehensive software environment for the visual display of geographically
registered environmental data sets, and to further enhance our cognitive abilities in emergency and disaster
decision-making. The related courses that I am taking are Human Centered System and Information(CSCE 655) and
Database System(CSCE 608).
8.3
SPENCER HUANG
Technical skills
Languages: Proficient in ASP.Net, C++, Java Perl, and Python; familiar with C++.
Technical knowledge: Apache-Tomcat server, Eclipse IDE, MS Visual Studio, MySQL database, Oracle database,
Oracle Weblogic server, Resin web server. Familiar with Java EE platform and ASP.net platform. Familiar with MS
Windows, Fedora and Ubuntu Linux and some knowledge of Cisco IOS.
Experience
Application Developer (Intern)
05/2010-08/2010
Cisco System
San Jose, United States
Joined the Business Unit of Enterprise Collaboration Platform (ECP).
Developed a Web-based testing automation tool using Java EE platform to improve integration testing effort for
OpenAPI team of ECP.
Application Developer
12/2006-04/2008
PChome-Skype
Taipei, Taiwan
Developed Servlet-related Web-based systems under Java EE platform.
Implemented and integrated systems using Enterprise Java Bean (EJB) along with Oracle Weblogic (formally BEA)
application server. Incorporated reusable components such as Spring and Hibernate framework as well.
Developed above mentioned systems in team settings; some projects were customer-centric, while others were
web-service for internal usage, and almost all required integration with existing Skype systems.
Quality Assurance Tester
10/2004-11/2006
Trend Micro
Taipei, Taiwan
Prepared test plan, test cases, and testing environment.
Conducted conformance testing and performance testing using Ciso/3Com equipments, Spirent testing
instruments, and Agilent testing instruments.
Implemented Perl/Shell script testing automation on Linux platform.
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Education
Texas A&M University
09/2009 – continue
College Station, Texas
Enrolled in the department of Computer Science and Engineering, in pursuit of M.S. in Computer Science.
Georgia Institute of Technology
08/2000 – 07/2004
Atlanta, Georgia
Graduated with B.S. in Computer Science; specialized in Networking, Database, and Software Engineering.
Research Area
My research area mainly focuses on Information Retrieval, specifically on the modeling and the analysis of large
social network. I have taken CSCE 670 Introduction to Information Retrieval and currently am taking CSCE 689
Internet Scale Data Management, in which both are taught by Prof. Caverlee. In the past, I have examined sites
such as YouTube and developed profile based search optimization via vector-space approach. Recently, the
semantic web and semantic tagging based applications have also become part of my research interest.
8.4
DHEEBAN SRINIVASAN GOVINDARAJAN
Technical Skills
Programming: Java, C, C++
Scripting Languages: Shell Scripting, JavaScript
Web: HTML, DHTML, CSS
Operating Systems: Windows, Linux
Experience
Research Intern, Indian Institute of Technology at Kharaghpur
Winter 2007
Study of various reputation based trust models for structured Topologies in Peer-to-Peer Networks.
Mentor: Asst. Prof. S.K Ghosh, Indian Institute of Technology, Kharagpur
Education
M.S in Computer Science
Texas A&M University, College Station, U.S.A
B.E in Computer Science and Engineering
Sri Venkateswara College of Engineering, Anna University, India
Exp. Spring 2012
Spring 2010
Research Area
I am interested in the intersection of Machine Learning, Information Retrieval and Web. I am also interested in
using visualization of Social Networks. The courses I am taking this Fall 2010 are: Internet Scale Data Management
(CSCE 689), Human Centered System and Interaction (CSCE 655) and Analysis of Algorithms (CSCE 629).
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REFERENCES
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