social web 2014: final presentations (part ii)

Group 16

The Reincarnation App

Filip Ilievski Sylvia van SchieWouter Stuifmeel

The Reincarnation App • A social web application to let you see who you were in previous lives • The Social Web • March 20th, 2014, VU University Amsterdam

GROUP

16

Introduction / ApproachTARGET Users of Facebook

GOAL Find the reincarnation chain of the user (all predecessors)

METHOD We hook up the user's date of birth to a person who deceased around the same date.

(margin up to three weeks)

VALUE The app is unique for it links data from Facebook to DBpedia and shows info about deceased people

It furthermore has a high entertainment value


Data flow


Data clustering


Clustering is based on the 8 results we received whenentering the initial birth date of 20 March 2007.

User interface


Group 19

Social Web - Facebook Activity Checker

Thomas Berger, Kristoffer Lie Braathen, Timo Nijhof

Vrije Universiteit Amsterdam

March 20th, 2014

mailto:thomas.berger@centrale-marseille.

What?How?Who?

What does it look like?

1 What?

2 How?

3 Who?

4 What does it look like?

Thomas Berger, Kristoffer Lie Braathen, Timo Nijhof Social Web - Facebook Activity Checker


What?How?Who?


Aim of the application

The overall goal is to explore when (ie: which days? what time?)users are the most active on Facebook.



What?How?Who?


Data mining

Pyhon script using Python SDK for Facebook;

Getting friends statuses and likes;

Categorize them, sum up all likes and statuses within acategory;

For the last week, sum up friends activities for each day.



What?How?Who?


Individual work

Thomas: Python code, documentation;

Timo: Charts, design of app, data integration anddocumentation;

Kristoffer: Charts, design of app, data integration anddocumentation.



What?How?Who?




Group 21

Concertify

Group 21

Bart Eijk, Theano Kotisi, Timur Carpeev

Structured data

Visualizations

Feature I: Clustering genres

blues-rock > blues & rock

viking metal > metal

synthpop > electronic & pop

Use pre-determined general tags blues, classical, country, dance, electronic, folk, hip-hop, indie, jazz, latin, metal, musicals, pop, reggae, rnb, rock

Feature II: Clustering venues

Classification: most occurring word (genre)

Bag of Words model based on clustered tags

{'blues': 0.0, 'classical': 0.0, 'country': 25.476190476190474, 'dance': 7.1428571428571423, 'electronic': 7.1428571428571423, 'folk': 25.476190476190474, 'hip-‐hop': 0.0, 'indie': 2.8571428571428572 ...

|  Limitations

{  Cold Start Problem/Popularity bias, ad hoc annotation behavior, weak labeling

{  Non-agreement on taxonomies

{  Ill-defined genre labels

{  Scalability of genre taxonomies

|  Scope

{  From taxonomies to folksonomies?

|  Evaluation

{  User Qualitative Evaluation of the Application

|  Future Work / Developments

{  Hierarchical Classification

{  Alternative Autotagging Models

{  Combining data sources: hybrid context - content systems for

music classification & recommendation

Group 22

Exploiting Twitter data for the automatic annotation of Dutch

Public TV ProgrammingGroup 22

Guido van Bruggen, Jochem Havermans, Shailin Mohan & Frank Schurgers

The Social Web 2014, VU Amsterdam | Final Presentation Social Web App

Goal:Helping the Netherlands Institute of

Sound and Vision to automatically annotate TV shows

Target user group:Clients of Sound and Vision

Advantages:

● Use of existing data;

● inexpensive;

● instantaneous annotation;

● easy to implement;

● automatic detection of hot topics;

● less need for tedious human annotation.

much advantage

wow

such cheap

very automatic

amaze

so data

Words per minute annotation

De Wereld Draait Door, 18-03-2014.Minute: 18:17.

Pauw en Witteman, 18-03-2014. Viewers: 778.000. Total tweets: 2231.

Additions

● Words per minute annotation

● fragmentation of episodes;

● access to tweet content of all tweets;

● normalizing tweet count with viewer

count;

Group 23

WhatsAround

“Be everywhere, anywhere!” Youssef Azriouil, Sara Chambel Pinheiro, Ana Rodrigues & Evangelia Marinaki

"Footprint - Where I've Been" is a designed map app for adding notes and marking

places

“Flickr” capture, create, and share

photos

“Instagram” way to capture and share the

world's moments

“Worldcam” easy way of finding photos

from a specific venue

WhatsAround

FAST GLOBAL FUN

Way to share your life and travels with friends, family and community

Easiest way of finding out what's happening right now, anywhere and everywhere

WhatsAround

Get user location

Serve up photos

Serve up place info

Send coordinates to

API (DataSets)

WhatsAround

Customized search

Different perspectives on a place

Be part of history by documenting

Chronological sequence - Understand the evolution of the place

Check your location in real time

No hashtags

Friends Vs Community

Clustering analysis

Photographers

Travellers

Active users of social web apps

SARA – Location Assessment

EVI – Instagram and Flickr API info retrieval

ANA – WikiLocation API connection

YOUSSEF – Mobile experience

Group 25

Group 25Jesse Groen, Alessio Muis, Ragaselvi

Ratnasingam

Our applicationFeatures of the applicationDataAnalysisIndividual features

Where is it used for?Connect common hashtags to usersFun!Enrich tweets

Clickable(Domain) RecommendationUser Dependent

Twitter data:HashtagsTimes usedFollowers & following

Cluster analysisTrends analysis

Jesse: Common hashtags among friends

Alessio: User dependent - Your own content

Selvi: Recommendation among yourconnections

AlessioSelviJesse@Group25

Thank you very much! #SW2014 #findyourhashtag #finalassignment

20 Mar via web

Favorite Retweet Reply

Group 26

GROUP 26-APP INTRODUCTION

• Goal: Find top popular places among my friends

• Function:

• 1. Filter different type of places

• 2. Find people from different countries like to go where?

• 3. Analyze our data

INDIVIDUAL WORK

• Annan Cheng: 1. Retrieve friends data from Facebook; 2.

Extract where friends have been from data; 3. Get friends

nationality through Google Geocoding API

• Jiahui Chen: Design the demo, realize the map, filter and

sequencing functions through Google map API, d3 and

JavaScript

• Ziyan Zong: Realize analyze data function by using different

visualization methods like histogram and pie chart, etc. Find

out meaningful and useful facts behind those data.

Group 27

Group 27Final assignment presentation

Data● Twitter streaming API● VeryRelated API

Approach● Search for query

○ Select most popular tweets○ Find most relevant terms○ Look for synonyms

● Select relevant terms○ Refine the query○ Update the results

Mockup

Added value● Interactive

○ Does suggestions● Intuitive

○ Clicking instead of typing● Interesting

○ 1 page overview

Group 29

Predicting attendance and outcome

of local elections - A web

applicationGroup 29:Remco DraijerRenee VaessenLily Martinez Ugaz

Description & Goal

• A web application

▫ Local elections on March 19th in the Netherlands

• Predicting outcome and attendance

▫ Based on number of tweets

• Functions as an informative app

• Investigates correlation between tweets and:

▫ Outcome (number of seats in municipal council)

▫ Attendance (turnout)

Approach

• Mining Twitter for location-based tweets

▫ Amsterdam, Den Haag, Rotterdam and Utrecht

• Nine parties selected

▫ All occur in four cities

• Extract tweets with party-name in text, user-name or user-description

▫ Preprocess data for duplicates and party-generated tweets

Data

• Twitter streaming API

▫ Fetch tweets during 24 hours

• Interactive visualizations with d3.js

• Results: correlation between % of seats in council and % of tweets about parties

▫ For Amsterdam, Den Haag, Rotterdam, Utrecht

• Distribution of tweets over mining period

Visualization

• http://www.remcodraijer.nl/socialweb/ass4/

Group 30

News TimelineThe Social Web 2014 - final assignment

Group 30

Motivation & Purpose

• information

• easy, visual way of getting up to speed

• easier than reading a newspaper or an RSS reader

• like a more visual, web-based, Flipboard

Data Sources

• media agencies around the world (list from Wikipedia)

• Twitter

• Bing image search

• Sentiment140

Data Flow• get the trending stories from the news agencies

• find tweets about the stories

• perform sentiment analysis on the tweets

• get images (and videos) related to the story

• export via JSON API

Data Flow• get the trending stories from the news agencies

• find tweets about the stories

• perform sentiment analysis on the tweets

• get images (and videos) related to the story

• export via JSON API

filtered by region and/or tag

Display

• Web app

• Mobile friendly

• Responsive gallery

• See a prototype at http://www.mihneadb.net/news_timeline/

http://www.mihneadb.net/news_timeline/

Group 31

The Social Web 2014 – Final assignment – G31: Jeroen Wever JWR970, Jeffrey Bruijntjes JBS257, Marije ten Brink MBK262

APPSPIRE!

What are his/her true aspirations?An entertaining way to discover dreams and desires of influential people… or your friends!


Goala. Discover aspirations of a person of your interestb. Compare your aspirations with othersc. Visualize aspirations in tag clouds or photo cloudsd. Find people who have specific aspirationse. Follow trends in our shared aspirations

Related work:Twitter Account Showdown


Approach: discover1. Retreive all tweets of user with Greptweet.com2. Clean up tweets, remove punctuation, stop words, links3. Use stemmer: matches verbs and nouns with same stem4. Use word list with aspirational verbs to extract tweets with aspirations5. Count occurrences of meaningful word

Other possible data sources: FB, blogs, Pinterest, Google+, ...


Approach: compareDetermine similarity between 2 users, based on amount of matching words: correlation


Approach: visualize

Tag cloud

Image cloud

Timeline

Group 32

Final Assignment: Group 32Francois Lelievre, Marek Janiszewski, Yahia El-Sherbini, David Marshall-Nagy

Main Concept

■ An easy to use application to manage your SoundCloud collection and enhance the social experience with music

Group Effort

■ Concept and Development: Marek and Francois

■ Concept and Testing: Yahia and David

Technical Background

■ Based on the SoundCloud API■ In-browser interface

Music Collection Overview

■ Check all my likes in one place■ Check all the tracks of a followed artist in

one place

Collection Management

■ Search for new songs■ Sort out and favorite your songs■ Follow artists

Song Recommendation

■ Based on the selected genre and on the likes of followed people

■ Based on the recent likes of the followed artists

■ Visualized search results

Thank You for Your Attention!

Questions?

social web 2014: final presentations (part ii)

Technology