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11th IEEE International Conference on Ubiquitous
  Computing and Communications (IUCC-2012)
         Liverpool, UK, 25-27 June, 2012




  Actualization of a
Course Library through
  Influential Twitter
      Knowledge


  Malinka Ivanova, Tatyana Ivanova
    Technical University of Sofia
  College of Energy and Electronics
Aim
To explore how the
collective intelligence of
Twitter users could
support a course library
list updating and
personalized learning
Content
• Microblogging, influential users
• Related work: Twitter use and influence
• Mechanisms for knowledge gathering
  and library list updating
  –   Using keywords
  –   Exploration of hashtags
  –   Tracking the favorite messages
  –   Utilization of Twitter lists
• Discussion and conclusion
Internet Technologies
                                 Problem definition

                                    static

                                    immutable
   current course library list

cover main topics
                                                  How do I reach the latest
            cover few additional problems         and novel information?
                                                     I have specific questions!

                                                       I have to solve a complex
                                                       problem!
                                                     How do I personalize
                                                     my course library list?
                                                How do I find valuable and
                                                relevant information sources?
Problem definition
                                                          new internet technologies

                                                             the latest solutions
                                                             emerging tools and
                                                             applications
dynamic course library list with streaming knowledge
                                                             relevant learning resource
  sharing, information   observation, discussions          good practices
  spreading, events      tracking, following shared
  announcing             content, keeping messages as
                         favorite




      Whether and how Twitter posts may be used to facilitate the learning process?
The hypothesis

         The influential users and
         trending microcontent
         according to analytical
         Twitter tools could be
         very powerful sources of
         useful and engaging
         knowledge for organizing
         an updated library list
• Influential Twitter users possess “personal
  attributes like credibility, expertise,
  enthusiasm and network attributes such as
  connectivity or centrality”.
  Bakshy, Hofman, Mason and Watts, 2011




 They influence their followers directly or
 indirectly through re-twitting cascades
Research questions
• “How can Twitter messages be mined for receiving
  suitable learning material from influential users?”
• “How could educators be supported in library lists
  updating?”
• “Are the most influential Twitter participants the
  heralds of novel and engaging information?”
Related Work
  “We found that the social aspect appears to be predominant
  in motivating users’ interactions”.
  Sousa, Sarmento and Rodrigues, 2010




Twitter tool “Eddi” for easy and
quick finding of popular topics by
searching, or navigating a tag
cloud, timeline or categories
Bernstein, Suh, Hong, Chen, Kairam and
Chi, 2010
Related Work
• Several studies about Twitter use for tracking various topics
  as:
   – Public health - Ailment Topic Aspect Model for Twitter is created
     to connect symptoms, treatments and general words with
     diseases
   Paul and Dredze, 2011
   – Earthquake shakes – algorithm monitoring tweets is presented
     and an earthquake reporting system in Japan is developed
   Sakaki, Okazaki and Matsuo, 2010

Domain and tack-sensitive filtering is used to eliminate
 false-positive tweets, a lot of tested techniques are
 domain-dependent
Related Work
• Hashtags usefulness in Twitter messages - Carter, Tsagkias and
  Weerkamp (2011) study multilingual hashtag characteristics and
  derived translation rules
• De Choudhury, Counts and Czerwinski (2011) define the important
  attributes for characterizing social media content on a given topic:
    • diffusion property

    • responsive nature

    • presence of external information

    • temporal relevance

    • thematic association of the tweet within a set of broadly defined categories

    • geographic dimension

    • authority dimension of the tweet creator

    • degree of activity of the tweet creator
Method
A literature list is created for the Internet Technologies
course following the next procedural steps:

 1. Formation of search queries through
the most suitable keywords that describe
the course focus – html, css, web design.


           2. Extraction of the relevant and
        influential Twitter users that could be
         sources of suitable learning content.

                    3. Applying analytical and measurement
                   tools to narrow down the most expedient
                     Twitter users for identification of novel
                   and emerging information and knowledge.
Experimentation

                                                     The library list is
                   tX                                seen as a Twitter
                                  H
                        tY   tZ                      user uL, forming an
                                                     ego-centric network
                                                     searching Twitter
tX                                                   users through
                                      tX
         tY   tZ        uL                           keywords K,
                                           tY   tZ   hashtags H, favorite
                                                     messages F and
     K                                               Twitter lists T
                                           F

                   tX             T
                        tY   tZ
Utilization of Keywords in a Search Query

                    • searching for Twitter posts
                      with relevant information
  Internet            pointing valuable sources
                      using “html”, “css” and
  Technologies        “web design” keywords
  course
                    • TweetLevel tool
                      (http://tweetlevel.edelma
                      n.com/) - used to gather
                      the 100 most influential
                      Twitter users and the most
                      tweeted words related to
                      “html”
Utilization of Keywords in a Search Query
    The 100 influential Twitter users – extraction and selection of useful users
• Mining the tweeted microcontent about related to “html” words:
  html 5, html tags, html form, design, html email, html code, psd file,
  web designer, basic html
• The experiment is repeated
    – 20 participants - the intersection between two different sets
      responding to the keywords “html & html5”
    – 11 users tweet content relevant to keywords “html & html code”
    – 1 user combines “html & basic html” keywords




  Keywords html & html5        Keywords html & html           Keywords html & basic
                               code                           html
Utilization of Keywords in a Search Query
     The 100 influential Twitter users – extraction and selection of useful users
• using the keyword “css” - the most shared links are to web
  designers/programmers sites with design elements, resources and
  tutorials, online news sites and developer tools
• Related words to “css” that are part of tweeted microcontent are: html,
  css framework, design, css animation, javascript, web design
• The selected keywords for further explorations: “css framework” and “css
  animation”
    – 6 influential Twitter users who use the keywords “css & css framework”
    – 6 influential Twitter users who include “css & css animation” keywords in their
      messages




    Keywords css & css framework                  Keywords css & css animation
Utilization of Keywords in a Search Query
     The 100 influential Twitter users – extraction and selection of useful users

• In the category “web design” - the most shared links are to web sites with
  resources, tools and tutorials, news web sites, blogs, and above found web
  sites in category “html”
• The frequently used keywords related to “web design” - web template,
  design process, website design, web designer, search engine marketing
• 15 users - the intersection between “web design” and “web template”




                       Keywords web design & web template
Utilization of Keywords in a Search Query
    The 100 influential Twitter users – extraction and selection of useful users
• 31 participants who tweet about “html & css”
• 14 Twitter users who frequently weave into their messages all three
  keywords “html”, “css” and “web design”
   – Excluded – 2 of them frequently post messages about new jobs and
     positions for web designers/programmers and 1 often tweets in
     languages other than English




                                                    Keywords html & css & web design
          Keywords html & css
Utilization of Keywords in a Search Query
          The 100 influential Twitter users – extraction and selection of useful users
                                                    •Further explorations - about the volume
                                                    and relevant value of the tweeted content
                                                    •They post an average amount of 440
                                                    messages per week – 84% tweets and 16%
                                                    re-tweets
                                                                         8 499                           3 659
                                                                       followers          1 web        followers
                                                               1 graphic                 designer
                                                               designer
                                                                                                      17 471
                                                                        16 097                       followers
                                                                       followers                1 web
                                                             2 web and                        developer
                                                                              35 084
                                                               graphic       followers
                                                             designers
                                                                                                        60 128
                                                                                       3 news and      followers
                                                                                          online      40 125
                                                                                       technology followers
                                                            25 198                       journals 553 822
                                                           followers
 Academics and educators teaching web                 3 representa-         7 474                  followers
programming and design are not in the final              tives of IT       followers

list of the most influential Twitter users              companies           3 967
                                                                          followers
Utilization of Keywords in a Search Query
               Extraction and selection of useful educators

• Twitter search tool - utilized to find relevant profiles of
  twitting professors and tutors




                                                Influence, popularity and engagement of
                                                educational society
24
                          Exploration of hashtags                              hours
  hashtags #html, #css and #webdesign - the Hash Tracking              858
  tool (http://www.hashtracking.com/) is utilized                     tweets
                                                                                     274 479
                                                                                    followers
                                                                       #html


• 4 users are selected as distributors of valuable and meaningful info
    – 3 web designers/programmers

         85%                              97%                    76%
                  15%                                                       24%
        tweets                           tweets     3% re-      tweets
                   re-                                                       re-
                                                    tweets                 tweets
                 tweets                                        80
      256                              308                               1
               1                                  1          tweets
     tweets                           tweets                            week
              week                               week

    – 1 writer about technology
                                         100%
                                        tweets
                              359                  1
                             tweets               week
Exploration of hashtags
Twitter              1st – 1724 2nd – 2934 3rd - 1327 4th - 26 902
user/messages        followers  followers  followers  followers
content
Links to tutorials   30%             17%             -               5%
and courses
Links to tips and    5%              3%              -               2%
codes
Blog and web sites   57%             33%             38%             73%
resources
News and events      1%              4%              3%              -
Irrelevant           7%              43%             59%             20%
messages to the
course
Other hashtags       #html5, #css,   #javascript,    #wordpress,     #cms,
                     #css3,          #programmers,   #template,      #wordpress,
                     #template,      #courses,       #design, #css   #design, #css,
                     #wordpress,     #web, #cms,                     #template,
                     #website,       #developer,                     #flash
                     #webdesign      #software,
                                     #beginners,
                                     #website,
                                     #dreamweaver
Exploration of hashtags                                 24
                                                                                  hours
                                                                          1353
•   5 interesting persons are selected                                   tweets
                                                                                     1 104
•   2 of them - the same distributors of knowledge who include in                     597
    their messages hashtag #html                                                   followers
                                                                          #css
•   1 of them = the most influential Twitter user when a keyword
    search is performed
•   2 new users
     – 1 technology interested person                   51%
                                                                 49%
                                                       tweets
                                                                  re-
                                                                tweets
                                                      91
                                                              1
     – 1 web designer/developer                     tweets
                                                             week
                                   97%
                                  tweets   3% re-
                                           tweets
                               500
                                         1
                              tweets
                                        week

•   an average of 37% of content includes links to blog posts and
    resources published on web sites
•    irrelevant messages are an average of 51%
Exploration of hashtags                                     24
                                                                           hours
• 4 unique twitting users in the area of web design             1500
  are chosen and examined                                      tweets
                                                                              1 043
   – 1 aggregation service collecting the resources                            080
     related to web design from blogs                          #web         followers
                                                               design
                      19%
                               81%
                     tweets
                                re-          75%
                              tweets                   25%
                                            tweets
                   500                                  re-
                            1
                  tweets                              tweets
                           week           396                         95%
                                                   1
                                         tweets                      tweets        5% re-
                                                  week
   – 1 online magazine for web design                                              tweets
   – 2 company representatives                                     500
                                                                              1
                                                                  tweets
• 64% of all their tweeted messages are useful links                         week
  to interesting web resources and 3% to tips and
  tutorials
                                                                    88%
• irrelevant messages are 33%                                      tweets
                                                                                12%
                                                                                 re-
• the often used hashtags are: #design,                                        tweets
  #socialmedia, #photoshop                                       499
                                                                            1
                                                                tweets
                                                                           week
Tracking the favorite messages
• Tracking the favorite messages -FavStar (http://favstar.fm/) tool                                1st
• 5 new users are extracted as valuable informative sources                          74%
• among the most favorite messages - links to tutorials, to articles, and           tweets
                                                                                              26%
  to web sites with useful stuff and resources                                                 re-
• 7 messages of the first Twitter user are among the most favorite –                         tweets
                                                                                  499
  the first message is favored 173 times, the rest of the messages are                     1
                                                                                 tweets
  favored as follows: 26 times, 25 times, 25 times, 20 times, 19 times                    week
  and 18 times.
                                                                  2nd                        3rd
 Twitter user 1st    2nd     3rd      4th   5th                                      93%
                                                             82%                    tweets   7% re-
                                                                        18%
                                                            tweets                           tweets
                                                                         re-
    number of   173,   7, 17   72, 17, 8,6,5,   3, 3,                  tweets      90
                                                          71                               1
    favorite    26,            18      5,4,3,   3, 3,                1           tweets
                                                        tweets                            week
    messages    25,                    3,3,3,   3, 3,               week
    for 3       25,                    3,3,3,   3
    months      20,                    3,3,3
                                                                           4th               5th
                19, 18
                                                            49%                      92%
                                                                       51%
    followers   31     4 275   3 627   3 084    965        tweets                   tweets   8% re-
                                                                        re-
                149                                                                          tweets
                                                                      tweets
                                                          53                     13twe
                                                                  1                        1
                                                        tweets                    ets
                                                                 week                     week
The number of favorite messages by followers
for a period of 3 months
Discovering users from Twitter lists
•   the most listed users - utilizing Listorious (http://listorious.com/) tool
•   3 lists are selected as most suitable, respectively with 11 062, 2 405, 1 707
    followers
•   4 users are chosen
•   the average usefulness and relevance of content in tweeted messages is 14.75%
    and it is the lowest value in comparison with the previous experiments

        №                   1st          2nd        3rd        4th
        tweets/week         219          64         17         58
        tweets, %           90           78         82         84
        re-tweets, %        10           22         18         16
        followers           21 190       24 451     552        2 682
        useful content, %   21           15         10         13
        position            Online       Informer   Web        Internet
                            technology   about      designer   and
                            journal      web        and        social
                                         design     teacher    media
                                                               strategist
DISCUSSION
• The latest layout of the course library list includes informative and
  knowledgeable resources tweeted by 36 users
    – 11 are in the top most influential people
    – 6 are active twitting educators found through keywords searching queries
    – 10 are chosen among the most impressionable persons weaving hashtags in
      their messages
    – 5 possess many favorite messages by their followers
    – 4 are found as useful and interesting for the course searching into categorized
      Twitter lists
                                                        Legend:
                                                        users selected by
                                                        keywords
                                                        educators selected by
                                                        keywords
                                                        users selected by
                                                        hashtags
                                                        users selected by
                                                        favorite messages
                                                        users selected from
                                                        Twitter lists
DISCUSSION
• An ego-centric network of the course
  library list is created - the weight of any
  edge is a summary value of Twitter users’
  influence, taking in consideration
  coefficients of influence, popularity and
  engagement (according to TweetLevel
  tool)
         • The influence - the number and authority of
           followers, the frequency of usernames
           mentioning and messages re-tweeted by
           others                                         Legend:
         • The popularity - number of followers,          users selected by
           following people and the lists number
         • Engagement - users’ activity, number of        keywords
           followers, number of username mentions and     educators selected by
           ratio broadcasting/engagement                  keywords
• With the highest value of influence are:                users selected by
                                                          hashtags
 the most influential people + users in Twitter lists >   users selected by
 users with many favored messages + users adding          favorite messages
                                                          users selected from
 hashtags > twitting educators found through keywords     Twitter lists
DISCUSSION
• The professions of the most valuable
  users for the course




• The main stream of learning materials
  comes from:
    – people practicing web
      design/programming,
    – following by IT companies’
      representatives, educators’ guild and
      journalists
• a new profession is forming of informers
  striving to discover news and to spread
  them among the best possible large
  audience
DISCUSSION
• Among the found valuable resources are:
tutorials                  blog posts sharing opinion and giving ideas

      novelty articles
                                                       useful codes and templates
tips for accomplishing small tasks and dealing
with tricky issues


                                 new tools and explanations of contemporary and
                                 emerging technologies


• Irrelevant messages vary between 7% and 59%
• The users who are most often placed in lists are
  among the influential persons, but they are with
  the lowest meaning of content for our library list
Conclusion


• Searching through keywords queries is still the most effective
  mechanism for gathering the needed information
• A small part of influential and impressionable Twitter users weave
  hashtags in their messages and in this way they stay invisible in
  searching through hashtags
• The combined search through keywords and hashtags does not give
  effective results
• Through the search via usernames and user profiles are achieved only
  partial results, because of not well formed self-description by Twitter
  users
• Very strong Twitter users for the course library list are found among
  the most influential users, the most favorite users and educators
  staying in the long tail of the Twitter stream
 Actualization the resources for learning through the proposed
  approach gives a possibility of forming a technology oriented and
  social media based library gathering the useful and the latest
  achievements in the examined area context
Conclusion



• Both tag-based and keyword-based search results include many
  irrelevant posts and it is necessary that some filtering of returned
  results or recommendations for searching be proposed to the
  educators
• This preliminary study could be used for developing such a filtering
  and recommendation system for making the process of searching of
  learning resources in the microblogging systems easier and more
  effective
• The findings point the importance of well formed profile of social
  web users, facts about their activities and the existence of the
  appropriate searching strategies for successful resources finding
• Consequently, a clear and explicit knowledge-based model of the
  users, as well as of the learning resources’ structure has to be
  created as a basis for building a searching and recommendation
  system
Thank you for your attention!

For contacts:
m_ivanova@tu-sofia.bg
tiv72@abv.bg


Image sources:
http://3.bp.blogspot.com/_-
      DyJ48htBV4/S87sOF6y7PI/AAAAAAAAFLE/Nk1k3yI_QCY/s1600/imagine_desktop_cascada1.jpg
http://www.kgaskinsconsulting.com/
http://good-trips.com/australia/royal_national_park/photos/eng
http://www.ncpc.org/resources/enhancement-assets/clipart-and-stock-art/red-apple-on-
      books.jpg/image_view_fullscreen
http://www.mylot.com/w/photokeywords/question+marks.aspx
http://thepoliticalcarnival.net/2012/03/02/friday-links-96/twitter-logo-4/
http://kennysilva.net/some-thoughts-on-influence/
http://www.squidoo.com/sea-shells
http://www.sodahead.com/fun/do-you-collect-seashells/question-
      1841673/?link=ibaf&q=&imgurl=http://img4.southernliving.com/i/2007/05/sanibel-island/seashells-l.jpg

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Actualization of a Course Library through Influential Twitter Knowledge

  • 1. 11th IEEE International Conference on Ubiquitous Computing and Communications (IUCC-2012) Liverpool, UK, 25-27 June, 2012 Actualization of a Course Library through Influential Twitter Knowledge Malinka Ivanova, Tatyana Ivanova Technical University of Sofia College of Energy and Electronics
  • 2. Aim To explore how the collective intelligence of Twitter users could support a course library list updating and personalized learning
  • 3. Content • Microblogging, influential users • Related work: Twitter use and influence • Mechanisms for knowledge gathering and library list updating – Using keywords – Exploration of hashtags – Tracking the favorite messages – Utilization of Twitter lists • Discussion and conclusion
  • 4. Internet Technologies Problem definition static immutable current course library list cover main topics How do I reach the latest cover few additional problems and novel information? I have specific questions! I have to solve a complex problem! How do I personalize my course library list? How do I find valuable and relevant information sources?
  • 5. Problem definition new internet technologies the latest solutions emerging tools and applications dynamic course library list with streaming knowledge relevant learning resource sharing, information observation, discussions good practices spreading, events tracking, following shared announcing content, keeping messages as favorite Whether and how Twitter posts may be used to facilitate the learning process?
  • 6. The hypothesis The influential users and trending microcontent according to analytical Twitter tools could be very powerful sources of useful and engaging knowledge for organizing an updated library list
  • 7. • Influential Twitter users possess “personal attributes like credibility, expertise, enthusiasm and network attributes such as connectivity or centrality”. Bakshy, Hofman, Mason and Watts, 2011  They influence their followers directly or indirectly through re-twitting cascades
  • 8. Research questions • “How can Twitter messages be mined for receiving suitable learning material from influential users?” • “How could educators be supported in library lists updating?” • “Are the most influential Twitter participants the heralds of novel and engaging information?”
  • 9. Related Work “We found that the social aspect appears to be predominant in motivating users’ interactions”. Sousa, Sarmento and Rodrigues, 2010 Twitter tool “Eddi” for easy and quick finding of popular topics by searching, or navigating a tag cloud, timeline or categories Bernstein, Suh, Hong, Chen, Kairam and Chi, 2010
  • 10. Related Work • Several studies about Twitter use for tracking various topics as: – Public health - Ailment Topic Aspect Model for Twitter is created to connect symptoms, treatments and general words with diseases Paul and Dredze, 2011 – Earthquake shakes – algorithm monitoring tweets is presented and an earthquake reporting system in Japan is developed Sakaki, Okazaki and Matsuo, 2010 Domain and tack-sensitive filtering is used to eliminate false-positive tweets, a lot of tested techniques are domain-dependent
  • 11. Related Work • Hashtags usefulness in Twitter messages - Carter, Tsagkias and Weerkamp (2011) study multilingual hashtag characteristics and derived translation rules • De Choudhury, Counts and Czerwinski (2011) define the important attributes for characterizing social media content on a given topic: • diffusion property • responsive nature • presence of external information • temporal relevance • thematic association of the tweet within a set of broadly defined categories • geographic dimension • authority dimension of the tweet creator • degree of activity of the tweet creator
  • 12. Method A literature list is created for the Internet Technologies course following the next procedural steps: 1. Formation of search queries through the most suitable keywords that describe the course focus – html, css, web design. 2. Extraction of the relevant and influential Twitter users that could be sources of suitable learning content. 3. Applying analytical and measurement tools to narrow down the most expedient Twitter users for identification of novel and emerging information and knowledge.
  • 13. Experimentation The library list is tX seen as a Twitter H tY tZ user uL, forming an ego-centric network searching Twitter tX users through tX tY tZ uL keywords K, tY tZ hashtags H, favorite messages F and K Twitter lists T F tX T tY tZ
  • 14. Utilization of Keywords in a Search Query • searching for Twitter posts with relevant information Internet pointing valuable sources using “html”, “css” and Technologies “web design” keywords course • TweetLevel tool (http://tweetlevel.edelma n.com/) - used to gather the 100 most influential Twitter users and the most tweeted words related to “html”
  • 15. Utilization of Keywords in a Search Query The 100 influential Twitter users – extraction and selection of useful users • Mining the tweeted microcontent about related to “html” words: html 5, html tags, html form, design, html email, html code, psd file, web designer, basic html • The experiment is repeated – 20 participants - the intersection between two different sets responding to the keywords “html & html5” – 11 users tweet content relevant to keywords “html & html code” – 1 user combines “html & basic html” keywords Keywords html & html5 Keywords html & html Keywords html & basic code html
  • 16. Utilization of Keywords in a Search Query The 100 influential Twitter users – extraction and selection of useful users • using the keyword “css” - the most shared links are to web designers/programmers sites with design elements, resources and tutorials, online news sites and developer tools • Related words to “css” that are part of tweeted microcontent are: html, css framework, design, css animation, javascript, web design • The selected keywords for further explorations: “css framework” and “css animation” – 6 influential Twitter users who use the keywords “css & css framework” – 6 influential Twitter users who include “css & css animation” keywords in their messages Keywords css & css framework Keywords css & css animation
  • 17. Utilization of Keywords in a Search Query The 100 influential Twitter users – extraction and selection of useful users • In the category “web design” - the most shared links are to web sites with resources, tools and tutorials, news web sites, blogs, and above found web sites in category “html” • The frequently used keywords related to “web design” - web template, design process, website design, web designer, search engine marketing • 15 users - the intersection between “web design” and “web template” Keywords web design & web template
  • 18. Utilization of Keywords in a Search Query The 100 influential Twitter users – extraction and selection of useful users • 31 participants who tweet about “html & css” • 14 Twitter users who frequently weave into their messages all three keywords “html”, “css” and “web design” – Excluded – 2 of them frequently post messages about new jobs and positions for web designers/programmers and 1 often tweets in languages other than English Keywords html & css & web design Keywords html & css
  • 19. Utilization of Keywords in a Search Query The 100 influential Twitter users – extraction and selection of useful users •Further explorations - about the volume and relevant value of the tweeted content •They post an average amount of 440 messages per week – 84% tweets and 16% re-tweets 8 499 3 659 followers 1 web followers 1 graphic designer designer 17 471 16 097 followers followers 1 web 2 web and developer 35 084 graphic followers designers 60 128 3 news and followers online 40 125 technology followers 25 198 journals 553 822 followers  Academics and educators teaching web 3 representa- 7 474 followers programming and design are not in the final tives of IT followers list of the most influential Twitter users companies 3 967 followers
  • 20. Utilization of Keywords in a Search Query Extraction and selection of useful educators • Twitter search tool - utilized to find relevant profiles of twitting professors and tutors Influence, popularity and engagement of educational society
  • 21. 24 Exploration of hashtags hours hashtags #html, #css and #webdesign - the Hash Tracking 858 tool (http://www.hashtracking.com/) is utilized tweets 274 479 followers #html • 4 users are selected as distributors of valuable and meaningful info – 3 web designers/programmers 85% 97% 76% 15% 24% tweets tweets 3% re- tweets re- re- tweets tweets tweets 80 256 308 1 1 1 tweets tweets tweets week week week – 1 writer about technology 100% tweets 359 1 tweets week
  • 22. Exploration of hashtags Twitter 1st – 1724 2nd – 2934 3rd - 1327 4th - 26 902 user/messages followers followers followers followers content Links to tutorials 30% 17% - 5% and courses Links to tips and 5% 3% - 2% codes Blog and web sites 57% 33% 38% 73% resources News and events 1% 4% 3% - Irrelevant 7% 43% 59% 20% messages to the course Other hashtags #html5, #css, #javascript, #wordpress, #cms, #css3, #programmers, #template, #wordpress, #template, #courses, #design, #css #design, #css, #wordpress, #web, #cms, #template, #website, #developer, #flash #webdesign #software, #beginners, #website, #dreamweaver
  • 23. Exploration of hashtags 24 hours 1353 • 5 interesting persons are selected tweets 1 104 • 2 of them - the same distributors of knowledge who include in 597 their messages hashtag #html followers #css • 1 of them = the most influential Twitter user when a keyword search is performed • 2 new users – 1 technology interested person 51% 49% tweets re- tweets 91 1 – 1 web designer/developer tweets week 97% tweets 3% re- tweets 500 1 tweets week • an average of 37% of content includes links to blog posts and resources published on web sites • irrelevant messages are an average of 51%
  • 24. Exploration of hashtags 24 hours • 4 unique twitting users in the area of web design 1500 are chosen and examined tweets 1 043 – 1 aggregation service collecting the resources 080 related to web design from blogs #web followers design 19% 81% tweets re- 75% tweets 25% tweets 500 re- 1 tweets tweets week 396 95% 1 tweets tweets 5% re- week – 1 online magazine for web design tweets – 2 company representatives 500 1 tweets • 64% of all their tweeted messages are useful links week to interesting web resources and 3% to tips and tutorials 88% • irrelevant messages are 33% tweets 12% re- • the often used hashtags are: #design, tweets #socialmedia, #photoshop 499 1 tweets week
  • 25. Tracking the favorite messages • Tracking the favorite messages -FavStar (http://favstar.fm/) tool 1st • 5 new users are extracted as valuable informative sources 74% • among the most favorite messages - links to tutorials, to articles, and tweets 26% to web sites with useful stuff and resources re- • 7 messages of the first Twitter user are among the most favorite – tweets 499 the first message is favored 173 times, the rest of the messages are 1 tweets favored as follows: 26 times, 25 times, 25 times, 20 times, 19 times week and 18 times. 2nd 3rd Twitter user 1st 2nd 3rd 4th 5th 93% 82% tweets 7% re- 18% tweets tweets re- number of 173, 7, 17 72, 17, 8,6,5, 3, 3, tweets 90 71 1 favorite 26, 18 5,4,3, 3, 3, 1 tweets tweets week messages 25, 3,3,3, 3, 3, week for 3 25, 3,3,3, 3 months 20, 3,3,3 4th 5th 19, 18 49% 92% 51% followers 31 4 275 3 627 3 084 965 tweets tweets 8% re- re- 149 tweets tweets 53 13twe 1 1 tweets ets week week The number of favorite messages by followers for a period of 3 months
  • 26. Discovering users from Twitter lists • the most listed users - utilizing Listorious (http://listorious.com/) tool • 3 lists are selected as most suitable, respectively with 11 062, 2 405, 1 707 followers • 4 users are chosen • the average usefulness and relevance of content in tweeted messages is 14.75% and it is the lowest value in comparison with the previous experiments № 1st 2nd 3rd 4th tweets/week 219 64 17 58 tweets, % 90 78 82 84 re-tweets, % 10 22 18 16 followers 21 190 24 451 552 2 682 useful content, % 21 15 10 13 position Online Informer Web Internet technology about designer and journal web and social design teacher media strategist
  • 27. DISCUSSION • The latest layout of the course library list includes informative and knowledgeable resources tweeted by 36 users – 11 are in the top most influential people – 6 are active twitting educators found through keywords searching queries – 10 are chosen among the most impressionable persons weaving hashtags in their messages – 5 possess many favorite messages by their followers – 4 are found as useful and interesting for the course searching into categorized Twitter lists Legend: users selected by keywords educators selected by keywords users selected by hashtags users selected by favorite messages users selected from Twitter lists
  • 28. DISCUSSION • An ego-centric network of the course library list is created - the weight of any edge is a summary value of Twitter users’ influence, taking in consideration coefficients of influence, popularity and engagement (according to TweetLevel tool) • The influence - the number and authority of followers, the frequency of usernames mentioning and messages re-tweeted by others Legend: • The popularity - number of followers, users selected by following people and the lists number • Engagement - users’ activity, number of keywords followers, number of username mentions and educators selected by ratio broadcasting/engagement keywords • With the highest value of influence are: users selected by hashtags the most influential people + users in Twitter lists > users selected by users with many favored messages + users adding favorite messages users selected from hashtags > twitting educators found through keywords Twitter lists
  • 29. DISCUSSION • The professions of the most valuable users for the course • The main stream of learning materials comes from: – people practicing web design/programming, – following by IT companies’ representatives, educators’ guild and journalists • a new profession is forming of informers striving to discover news and to spread them among the best possible large audience
  • 30. DISCUSSION • Among the found valuable resources are: tutorials blog posts sharing opinion and giving ideas novelty articles useful codes and templates tips for accomplishing small tasks and dealing with tricky issues new tools and explanations of contemporary and emerging technologies • Irrelevant messages vary between 7% and 59% • The users who are most often placed in lists are among the influential persons, but they are with the lowest meaning of content for our library list
  • 31. Conclusion • Searching through keywords queries is still the most effective mechanism for gathering the needed information • A small part of influential and impressionable Twitter users weave hashtags in their messages and in this way they stay invisible in searching through hashtags • The combined search through keywords and hashtags does not give effective results • Through the search via usernames and user profiles are achieved only partial results, because of not well formed self-description by Twitter users • Very strong Twitter users for the course library list are found among the most influential users, the most favorite users and educators staying in the long tail of the Twitter stream  Actualization the resources for learning through the proposed approach gives a possibility of forming a technology oriented and social media based library gathering the useful and the latest achievements in the examined area context
  • 32. Conclusion • Both tag-based and keyword-based search results include many irrelevant posts and it is necessary that some filtering of returned results or recommendations for searching be proposed to the educators • This preliminary study could be used for developing such a filtering and recommendation system for making the process of searching of learning resources in the microblogging systems easier and more effective • The findings point the importance of well formed profile of social web users, facts about their activities and the existence of the appropriate searching strategies for successful resources finding • Consequently, a clear and explicit knowledge-based model of the users, as well as of the learning resources’ structure has to be created as a basis for building a searching and recommendation system
  • 33. Thank you for your attention! For contacts: m_ivanova@tu-sofia.bg tiv72@abv.bg Image sources: http://3.bp.blogspot.com/_- DyJ48htBV4/S87sOF6y7PI/AAAAAAAAFLE/Nk1k3yI_QCY/s1600/imagine_desktop_cascada1.jpg http://www.kgaskinsconsulting.com/ http://good-trips.com/australia/royal_national_park/photos/eng http://www.ncpc.org/resources/enhancement-assets/clipart-and-stock-art/red-apple-on- books.jpg/image_view_fullscreen http://www.mylot.com/w/photokeywords/question+marks.aspx http://thepoliticalcarnival.net/2012/03/02/friday-links-96/twitter-logo-4/ http://kennysilva.net/some-thoughts-on-influence/ http://www.squidoo.com/sea-shells http://www.sodahead.com/fun/do-you-collect-seashells/question- 1841673/?link=ibaf&q=&imgurl=http://img4.southernliving.com/i/2007/05/sanibel-island/seashells-l.jpg