2012 1030 presentation for sentiment conference

Post on 07-May-2015

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I only had 7 minutes and it was right before lunch, hence the bread analogy. I focused on one of DataSift's truly unique features---the ability to do real time sentiment analysis on Social Content. Email me at rob.bailey@datasift.com if you'd like to learn more.

transcript

Using Social Sentiment to

Track Real Time Public

Opinion

Rob BaileyCEO, Datasift

rob.bailey@datasift.comTwitter: @RMB

Most Powerful Platform For Real Time Social

We ingest petabytes of Social data from

50+ global sources in Real Time with fully redundant, push-based systems

1. Ingestion

Each Social item gets tagged 40+

different ways (eg with Klout score)

in <300 milliseconds

3. Enrichment & Filtering

Enriched, filtered data is sent back

out through enterprise grade

API to 250+ customers

4. Distribution2. Cleaning & Normalization

Using proprietary technology, we

scrub the data to eliminate

noise/spam & normalize it

We do all of this in about half a second.

2

Sentiment in Social Is Like Bread

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Sentiment in Social Is Like Bread

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Fresh is better.

Freshest Sentiment Analysis

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• We filter in real time, with latency < 300 MS

• Set up new filters in minutes

• Currently work with Lexalytics

• We cover English, German, Portuguese, Spanish, French

• 10 more languages coming

Benefits of Real Time Sentiment

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• Capture events in real time

• Instantaneous drill-downs on drivers

• Beat the competition (News, Finance)

• Understand your audience faster

CASE STUDY: US Presidential Debates

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• Both candidate’s sentiment levels dropped when they attacked

• Obama scored big with the bayonet comment• Delayed drop for Romney with Syrian & sea comment

CASE STUDY: Women Hate RIM

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Women were better predictors than men about negative market reaction to the news.

CASE STUDY: Facebook IPO

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Public sentiment on Twitter was a strong indicator of where the stock price would move

next.

Sentiment in Social Is Like Bread

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Not everyone can handle it.

Hard To Replicate Technical Infrastructure

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We ingest data from over 50 Social sources & 850+ news sources in real time & use redundant systems to compensate for sometimes unreliable partner APIs

Pickle is our massively parallel and scalable cluster of virtual machines that interprets, compiles and evaluates customer-created filters (expressed in CSDL) against every single incoming message

Augmentations covers all of the data services which either perform a real-time data analysis or lookup data from 3rd

party data sets of pre-computed data.

We use a variety of queing technologies including RabbitMQ to ensure constant flow of data

Our billing platform manages licenses & billing across hundreds of customers and 50+ content sources in real time, 5 min increments

Our data store is based upon a bespoke deployment of Hadoop/HBase and our own low level Virtual Machine.

Currently we have 1 Petabyte's of storage & are the only company worldwide to offer 2+ years of historical Social data

We deliver real-time data with very low latency (sub 200ms that our platform adds.) data through our HTTP streaming engine called 'Meteory' that is built on Node.JS

DataSift Infrastructure Highlights

Why Real Time So Important

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• Catch problems before they explode

• Set up new searches quickly

• Competitors are watching

• Customers are increasingly impatient

Sentiment in Social Is Like Bread

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GET STARTED: hello@datasift.com

GET INFORMED: @RMB