collating social network profiles

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Collating Social Network Profiles. Objective. System. . . . Objective. System. Input. Output. . Social Network Profiles. - PowerPoint PPT Presentation

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Collating Social Network Profiles

2

<Twitter Profile, Facebook Profile, G+ Profile, …>

Objective

<Company Name> System<Twitter Profile, Facebook Profile, G+ Profile, …>

3

<Twitter Profile, Facebook Profile, G+ Profile, …>

Objective

Company Name SystemSocial Network

Profiles

Input Output

4

Record Linkage+

Identity

5

Agenda

Introduction Objective

Contrast to Existing Work

Work Done Baseline System

Individual Network Approach

Machine Learning Experiments

Next Steps, Q&A

6

Baseline System

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Ground Truth

Two networks: Facebook and TwitterTop seventy 2013 Fortune 500 companies

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Baseline Algorithm

1.Take company name.

2.Search Facebook/Twitter API using it.

3.Return first result from each.

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Baseline Performance

Facebook Twitter Both0

10

20

30

40

50

60

70

34

52

30

Corr

ect

Matc

hes

10

Individual Network Approach

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New Approach

Score profiles based onEdit Distance

Company Name – Username

Company Name – Display Name

Relative Popularity

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Display Name

Username

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New Approach

Score profiles based onEdit Distance

Company Name – Username

Company Name – Display Name

Relative Popularity

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Scoring

Edit Distance Score:

Popularity Score:

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Best Performing Combination

Facebook Twitter Both0

10

20

30

40

50

60

70

34

52

30

40

50

34

Baseline Username Edit Distance + Popularity

Corr

ect

Matc

hes

16

Machine Learning Experiments

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Freebase Ground Truth

1,422 with a social media presence

917 with Facebook, 687 with Twitter

598 with both

553 with valid profiles

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Training Set

553 Correct

553 Incorrect

1106

Total

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Cross Validation Results

Classifier Test | Train Train | Test

Linear Regression 0.734 0.707

Gaussian Naïve Bayes 0.972 0.956

Multinomial Naïve Bayes 0.511 0.506

Bernoulli Naïve Bayes 0.720 0.701

Decision Tree 0.954 0.935

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Next Steps

Improve training set: provide harder examples

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Next Steps

Improve training set: provide harder examplesIncorporate more profile data

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Next Steps

Improve training set: provide harder examplesIncorporate more profile dataBuild system around classifiers

23

Agenda

Introduction ObjectiveContrast to Existing Work

Work Done Baseline SystemIndividual Network ApproachMachine Learning Experiments

Next Steps, Q&A

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