Online Trends Analysis - itnig friday

Online trends Analysis Francesc Gomez-Morales @francescgo [email protected] me.francescgo.com

#itnigfridays

WHO AM I?

Analy/cal Heart & Mashup Mind

2007 2008 2009 2010 2011 2012 2013

LET’S ASSUME YOU KNOW WHAT YOU’RE TALKING ABOUT…

Web is about measurement

Too many things to measure

Gatorade Mission Control

A framework proposal (from a marke/ng perspec/ve)

hBp://www.flickr.com/photos/nocallerid_man/

Web Analysis Framework (Marke/ng perspec/ve)

On-‐site

Owned Media

Web Page

“Web Analysis”

Google Analy/cs / Kissmetrics / CrazyEgg (…)

Social Media and other

Public Profiles

“Social Media Analysis”

Facebook insights / SocialBro / Bit.ly (…)

Off-‐site

Compe/tors owned media

Web Page

Web Compe//ve Intelligence

Alexa / Compete / Builtwith

Social Media and other

Public Profiles

Social Media Compe//ve Intelligence

SocialBakers / DKS Social Smart

Consumers media

Web Pages and Social

Media Profiles

Web Monitoring or netnography

Radian6 / Brandchats / Websays /

Google Trends

Search Engines

Organic

SERP Monitoring

SEOmoz / Link Assistant / Raventools

Paid

PPC Campaigns Monitoring

Semrush / Wordstream

Let’s focus on trends

hBp://www.flickr.com/photos/20116729@N00/

What the trend?

A trend (fad) is any form of behavior that develops among a large popula/on and is collec/vely followed with enthusiasm

for some period (generally as a result of the behavior's being perceived as novel in some way)

Sociology in a Changing World By William Kornblum, Carolyn D. (COL) Smith Page 213

WHY TRENDS & MEMES ARE NOW SO TRENDING?

Thank you, Tim Berners-‐Lee

Massive adopYon of online services has contributed to the unique and unprecedented possibility of register and analyze micro-‐trends

in almost-‐real-‐Yme

hep://www.flickr.com/photos/rishibiswas/

Key technological innova/ons (IMHO) hep://www.flickr.com/photos/rishibiswas/

Rich Internet Applica/ons (RIA) ex. Use of javascript

Web-‐oriented Arquitecture (WOA)

Apache Hadoop + MapReduce + Google File System

The biggest Social Graph in human history

One graph to rule them all!

Visualize your own graph

heps://apps.facebook.com/touchgraph/

TALKING ABOUT TRENDS IS TALKING ABOUT PEOPLE

People and trends Diffusion of Innova/ons, 5th Edi/on Everee M. Rogers 2003

Social Technographics •  Trends are generated by

people’s ac/vity

•  Social Technographics classifies people according to how they use social technologies

•  Forrester's Social Technographics data classifies consumers into seven overlapping levels of social technology par/cipa/on

People and trends > Social Technographics

hep://empowered.forrester.com/ladder2010/

People and trends > Social Technographics

Forrester Ladder

Differences between countries People and trends > Social Technographics

Different between Ages People and trends > Social Technographics

all animals are equal… People and trends > Influence

… but some animals are more equal than others

klout People and trends > Influence

hep://klout.com/

klout People and trends > Influence

hep://klout.com/#/topic/social-‐media

SOURCES OF TRENDS

Sources of trends

•  Every single ac/vity on the web is registered and could be analyzed

•  Different ac/vi/es, different sources of trends

•  The more “passive” behaviour, the easiest analysis. Analyze Visits is simplier than analyze blog posts.

Sources of trends: classifica/on by user ac/vity

Creators

Conversa/onalists

Cri/cs

Collectors

Joiners

Espectators

Inac/ves Forrester Ladder

Ranking of the main social networking sites

Sources of trends > Visits/Pageviews of websites/content

Top sites in spain -‐ Sept 14, 2013


Top sites by niche

hep://www.alexa.com/topsites/category/Top/Sports/Table_Tennis


heps://adwords.google.com/da/DisplayPlanner


Youtube Consump/on in Spain


hep://www.socialbakers.com/youtube-‐sta/s/cs/country/spain/

hep://youtube.com/trendsmap


hep://www.youtube.com/trendsdashboard


hep://google.com/trends/explore

Sources of trends > Use of keywords in search engines


hep://google.com/trends/explore



hep://appannie.com/matrix

Sources of trends > Installa/on of mobile apps


hep://appfigures.com/reports/ranking


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hep://appfigures.com/reports/reviews

hep://www.appdata.com/

Sources of trends > Use of social games or social apps

hep://www.appdata.com/

Sources of trends > Use of social games or social apps

Top10 stories of the day (From May 24, 2007 to May 23, 2008)

Sources of trends > News aggregators ac/vity

hep://www.chrisharrison.net/index.php/Visualiza/ons/DiggRings

hep://www.socialbakers.com/facebook-‐pages/celebri/es/spain/

Sources of trends > Social support of profiles

Celebri/es in Facebook (Spain)

hep://www.socialbakers.com/facebook-‐pages/celebri/es/spain/


Poli/cs in Twieer (Spain)

hep://www.socialbakers.com/facebook-‐pages/7703918541-‐internet-‐explorer


hep://www.pagedatapro.com/pages/leaderboard/tac/tac_wg


hep://es.favstar.fm/all-‐/me-‐most-‐favorited-‐tweets

Sources of trends > Support and/or Difussion of content

hep://es.favstar.fm/all-‐/me-‐most-‐retweeted-‐tweets



hep://monitor.wildfireapp.com/count_reports/display?facebook


hep://twtrland.com/

Sources of trends > Find Places and Check-‐in

hep://www.4sqmap.com

Sources of trends > Use of keywords in Twieer

hep://trendsmap.com/


hep://trends24.appb.in/barcelona


hep://whaehetrend.com/top10

The business of trends

heps://blog.twieer.com/2013/study-‐the-‐value-‐of-‐promoted-‐trends

Sources of trends > Contribu/ons to open source projects or wikis

hep://artzub.com/ghv/#repo=jquery&user=jquery


heps://github.com/twbs/bootstrap/contributors


heps://github.com/twbs/bootstrap/graphs/code-‐frequency


heps://github.com/twbs/bootstrap/graphs/punch-‐card


hep://notabilia.net/

Top 100 most controversial ar/cles in English Wikipedia


hep://gigapan.com/gigapans/4277

Top 100 most controversial ar/cles in English Wikipedia


hep://wikiproject.oii.ox.ac.uk/mapping_wikipedia

Number of words of english geolocated Wikipedia ar/cles

Sources of trends >Adop/on of technology

hep://trends.builtwith.com


hep://trends.builtwith.com/analy/cs

Top 10k websites Top 1M websites


heps://trends.builtwith.com/widgets/Facebook-‐Like

TREND DYNAMICS

Meme/cs

Cultural traits are transmieed from person to person, similarly to genes or viruses. Cultural evolu/on therefore can be understood through the same basic mechanisms of reproduc/on, spread, varia/on, and natural selec/on that underlie biological evolu/on.

Trend Dynamics > Meme/cs

Cultural EvoluYon and MemeYcs Francis Heylighen & Klaas Chielens hep://pespmc1.vub.ac.be/Papers/Meme/cs-‐Springer.pdf

Meme

Cultural replicator; a unit of imita/on or communica/on

Trend Dynamics > Meme/cs > Meme

The Selfish Gene (2nd ediYon) Dawkins, R. (1989) Oxford University Press.

1. Longevity 2. Fecundity 3. Copying-‐Fidelity

Memeplex

Collec/on of mutually suppor/ng memes, which tend to replicate together

Trend Dynamics > Meme/cs > Memeplex

Cultural EvoluYon and MemeYcs Francis Heylighen & Klaas Chielens hep://pespmc1.vub.ac.be/Papers/Meme/cs-‐Springer.pdf

Memes and trends Trend Dynamics > Meme/cs

Memes

Trends

Meme Dynamics Trend Dynamics > Meme/cs

Assimila/on • No/ce • Understand • Acceptance

Reten/on •  longevity

Expression • Speech • Text • …

Transmission • Internet • Mass Media

Meme Dynamics Trend Dynamics > Meme/cs

Assimila/on

Reten/on

Expression

Transmission

Meme Fitness

The anatomy of a (Twieer) trend

Main takeaways: •  the resonance of the content with the users of the social network plays a

major role in causing trends •  a majority of the content propagated to cause trends arise from tradi/onal

media sources

Trend Dynamics > Twieer Trending Topics > The anatomy of a trend

The way the trends dissipate fits a normal distribu/on

16.32 million tweets on 3361 different topics over 40 days in Sep-‐Oct 2010


The decay factor of a trend is 1/t Trend Dynamics > Twieer Trending Topics > The anatomy of a trend

Example A trending topic with 10.000 tweets/hour How many tweets will have axer 5 hours? N(t=0) = 10.000 tweets t = 5 hours N(t=5) = N(t=0)·∙[1/t] = = 10.000 ·∙ 1/5 = 2000 tweets

Almost every trending topic is short Trend Dynamics > Twieer Trending Topics > The anatomy of a trend

Strong rela/on between influencers and trending topics

Rela/on between authors and ac/vity: •  No propagaYon, no trend Correla/on between number of unique authors with the dura/on (0.8)

•  No people retweeYng, no trend The number of retweets for a topic correlates very strongly (0.96) with the trend dura/on

•  Many influencers, longer trends Nega/ve correla/on of −0.19 between the domina/on-‐ra/o of a topic to its trending dura/on (The domina/on-‐ra/o for a topic can be defined as the frac/on of the retweets of that topic that can be aeributed to the largest contribu/ng user for that topic)


Twieer doesn’t generate news, but does filter them

Social media, far from being an alternate source of news, func/ons more as a filter and an amplifier for interes/ng news from tradi/onal media


(Twieer) Informa/on diffusion

Main takeaways: •  the resonance of the content with the users of the social network plays a

major role in causing trends •  a majority of the content propagated to cause trends arise from tradi/onal

media sources

Trend Dynamics > Twieer Trending Topics > Informa/on Diffusion

Very few people follow or are followed by many users

15 million URLs exchanged among 2.7 million users over a 300 hour period

Both the in-‐degree (followers) and the out-‐degree (followee) distribu/ons have /ght log-‐normal fits


Twieer is a small world 15 million URLs exchanged among 2.7 million users over a 300 hour period

Twieer graph is a small world with a mean directed path length of 3.61


The majority of users has low ac/vity Trend Dynamics > Twieer Trending Topics > Informa/on Diffusion

The majority of URLs have no resonance

If your URL appears in 10 different users, then it's more popular than 99.9% of the rest of URL tweeted


Only a very few tweets has several cascades of retweets

RT-‐cascades (the user men/ons the source) F-‐cascades (the user men/ons the source and is its follower) Each cascade consists of one or more subcascades. The number of subcascades per cascade is power-‐law distributed


How big are subcascades?

For each cascade the subcascades not only vary in number, but also in size.


If your tweet is interes/ng is more likely that I will follow you

The distances to the root are short, even when compared with the already short average path length in the follower graph. One hypothesis explaining this data could be that when a user receives some interes/ng URL along an path longer than 1, then that user is very likely to start following the original source of the URL


The more users, the bigger the subcascades

The URLs tweeted by the highly connected users reach large audiences and are likely to be (re)tweeted by their followers. However, the causality is likely to be bidirec/onal: the users’s URLs are tweeted more because they have many folllowers, but also they have accumulated many followers because what they tweet tends to be interes/ng and viral.


How long takes to make a RT? The diffusion delay taken across all the (u, i) pairs in the social graph is log-‐normally distributed with a median of 50 minutes


TREND PARAMETRIZATION

Trending Topic Classifica/on Trend Parametriza/on

TwiBer Trending Topic ClassificaYon Kathy Lee, Diana Palse/a, Ramanathan Narayanan, Md. Mostofa Ali Patwary, Ankit Agrawal, and Alok Choudhary 2011 11th IEEE Interna/onal Conference on Data Mining Workshops

768 trending topics selected randomly from the +23000 collected between 2010 and 2011

Classifica/on Tecniques Trend Parametriza/on

Comparison of classifica/on accuracy using different classifiers for network-‐based classifica/on


Classifica/on Tecniques Trend Parametriza/on

Comparison of classifica/on accuracy using different classifiers for text-‐based classifica/on


NBM = Naive Bayes Mul/nomial SVM = Support Vectors Machines (number of tweets, top frequent terms)

“Online Trends Analysis” by Francesc Gómez Morales is licensed under a Crea/ve Commons Aeribu/on-‐NonCommercial-‐ShareAlike 3.0 Unported License

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Online Trends Analysis - itnig friday