sentimental market segmentation

8/13/2019 Sentimental Market Segmentation

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Sentimental Market Segmentation

Shlomo Argamon, Ph.D.

CEO & Cofounder, Subtext3

Based on a presentation given at

Sentiment Analysis SymposiumApril 13, 2010, New York, NY


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http://www.subtext3.com

Lots of sentiment analysis


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Why??Lots of sentiment analysis


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Why sentiment analysis

What are they thinking?

What do they want?

What will they buy?


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Wheres the ROI?

What should I fix?

Find comparatively negative aspects of my

product or positive areas about competitors

Howm I doing?

Examine sentiment trends to examine effects of

marketing or new products

Wheres the action? Find the customersunfulfilled needs


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Perceptions

Choices

Products &

Features

Advertising

Potential

Customer

Opinions

Texts

Needs &

Wants

Customer Model


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PerceptionsProducts &

Features

Advertising

Potential

Customer

Opinions

Texts

Needs &

Wants

Choices

Customer Model



Products &

Features

Advertising

Potential

Customer

Opinions

Texts

Needs &

WantsPerceptions

Perceptions

Perceptions

Choices

Customer Model



Products &

Features

Advertising Opinions

Texts

Needs &

WantsPerceptions

Perceptions

Perceptions PotentialCustomer

Potential

Customer

Potential

Customer

Potential

Customer

Choices

Customer Model


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Market Segmentation

Product/brand segmentation

What products are close to which?

Based on customer needs and perceptions, notproduct features

Customer/community segmentation

Meaningful subsets of potential customers

Relative to a given market!

Know their characteristics



Perceptual Maps



CommunityMaps



Understand The Community

Not just whatthey are sayingWhois saying it?

What groups of people have similar

opinions (about X)?

What kinds of people are they?

Howdo they see things? How do they group products, brands, or

features?



Varieties of Sentiment Analysis



DocumentFilter(topic, source)

SentimentClassifier

Positive

Negative

Neutral

Trend

Snapshot

Multidimensional



Sentiment

Finder

Topic

Classifier

Topic/Sentiment

Correlation

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Coke Pepsi RC

Neutral

Negative

Positive

Trend

Snapshot

Multidimensional



Sentiment

Finder

Target

Finder

Target/Sentiment

Correlation

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Coke Pepsi RC

Neutral

Negative

Positive

Trend

Snapshot

Multidimensional



But

Who are they and what do they think

We still need

More detail on their opinions

Profiles of the writers



Detailed

Sentiment

Finder

Target

Finder

Sentiment

Complexes

Demographic

Profiling

Demographic Trends

Perceptual Map

Customer Map


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Detailed Sentiment Finding

Based on research in the Linguistic Cognition Lab

at Illinois Institute of Technology

http://lingcog.iit.edu
http://lingcog.iit.edu/http://lingcog.iit.edu/


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Different kinds of sentiment


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Different kinds of sentiment

This uniquedog or chicken housewasmade with green practices in mind.

PositiveAppreciation

Valuation

Oh, and on principle Ihateextremists /zealotsof any ilk.

NegativeAffect

Affection

...if your sitelooks a complete mess then

you will loose[sic]that visitor for good.

NegativeAppreciation

Quality

Oh and Spooks, with this really tough

and sexy old ladyin it, kicking ass.

PositiveJudgment

Tenacity


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Syntactic connections


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More sentiment expressions

[I]evaluator[couldnt]polaritybring myselfto [like]attitude

[him]target.

[It]target-1is [not]polarity[as [good]attitudeas]comparator[theMinolta D7]target-2.

[Gap.Com]targetis an [excellent]attitudeexample of [aretailer]superordinate[using its online shopping store as an

extension and expansion of its retailing]aspect.


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Detailed sentiment finding

Texts

LexiconLinkage

Rules

ComplexSentiment

Expressions

Dependency

Parsing

Syntactic

Relations

Find

Chunks

(attitudes,targets,

hinges,)

ChunksExpression

LinkageDisambiguation


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Demographic Profiling


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Authorship Profiling

Infer things about the author from the style of

the language

Gender

Age

Native language

Personality type

Education level

Etc


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Capturing language style

Linguistic variation independent of the topic Function words

Parts-of-speech

Syntactic structures Morphology

Linguistic complexity

Vocabulary size

Mistakes

Slang


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Male/Female Classification

20th Century narrative fiction: 79%

20th Century non-fiction: 83%

21st Century blogs: 77%

17th-19th Century French lit.: 76%

Male Features Female Features

the, this, that, those,as, one, of, to,

prepositionsadjectives numbers

she, for, with, not, and,in, I, you, pronounspresent-tense-verbs


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Other dimensions

Native language: ~80%

Personality:

Neuroticism: ~68%

Extraversion: ~55-70%


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Simple Prototype

53,983 blog snippets from the ICWSM task

corpus (Aug-Sep, 2008)

268,665 sentiment expressions found

Examples:

I think that Sarah [Palin]targetwould be a

[terrible]attitude[vice president]superordinate

[the game]targetwas [too simplistic]attitude[to serve as

proper material for argument]aspect


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Authorship Profiling

Gender (Male/Female)

Age (Younger/Older)

Based on features from previous studies

Education level (LowerEd, MediumEd, HigherEd)

Based on linguistic complexity


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Trend Analysis


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Apartment sentiment by gender

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apartment/Female

apartment/Male


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Apartments - gender difference

apartment/Male-Female

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McCain & Palin - gender difference

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mccain/Male-Female

palin/Male-Female


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Perceptual Map - Relationships


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Perceptual Map - Relationships


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Perceptual Map - Issues


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Sentimental Market Segmentation

Construct perceptual and community maps, by: Detailed extraction of sentiment expressions

Semantic and structural detail

Authorship profilingTells us what kinds of people are writing which opinions

(Also need to attribute third-party sources)

Dimensionality reduction over author opinions and

profiles (PCA, MDS, etc.)


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Thank you

Contact us:

Shlomo Argamon

[email protected]@ShlomoArgamon


sentimental market segmentation

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