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

7

Ground Truth

Two networks: Facebook and TwitterTop seventy 2013 Fortune 500 companies

8

Baseline Algorithm

1.Take company name.

2.Search Facebook/Twitter API using it.

3.Return first result from each.

9

Baseline Performance

Facebook Twitter Both0

10

20

30

40

50

60

70

34

52

30

Corr

ect

Matc

hes

10

Individual Network Approach

11

New Approach

Score profiles based onEdit Distance

Company Name – Username

Company Name – Display Name

Relative Popularity

12

Display Name

Username

13

New Approach

Score profiles based onEdit Distance

Company Name – Username

Company Name – Display Name

Relative Popularity

14

Scoring

Edit Distance Score:

Popularity Score:

15

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

17

Freebase Ground Truth

1,422 with a social media presence

917 with Facebook, 687 with Twitter

598 with both

553 with valid profiles

18

Training Set

553 Correct

553 Incorrect

1106

Total

19

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

20

Next Steps

Improve training set: provide harder examples

21

Next Steps

Improve training set: provide harder examplesIncorporate more profile data

22

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