[Colloq] Thesis Defense - Susan Collins - Wednesday, February 4, 4pm, 366 WVH - Predicting Satisfaction with Life from Facebook

[Fong, Andy]

Topic: Thesis defense
Title: Predicting Satisfaction with Life from Facebook
Speaker: Susan Collins
Date: Wednesday, February 4, 2015
Time: 4:00pm to 5:00pm

Location: 366WVH

Abstract:
Social media can be beneficial in detecting early signs of emotional difficulty.
We utilized the Satisfaction with Life (SWL) index as a cognitive
health measure and presented models to predict an individual's SWL.
Our models considered ego, temporal, and link Facebook features collected
through the myPersonality.org<http://myPersonality.org> project. We demonstrated the strong correlation
between Big 5 personality features and SWL, and we used this insight
to build two-step Random Forest Regression models from ego features. As
an intermediate step, the two-step model predicts Big 5 features that are
later incorporated in the SWL prediction models. We showed that the twostep
approach more accurately predicted SWL than one-step models. By
incorporating temporal features we demonstrated that "mood swings" do
not affect SWL prediction and confirmed SWL's high temporal consistency.
Strong link features, such as the SWL of top friends or significant others,
increased prediction accuracy. Our final model incorporated ego features,
predicted personality features, and the SWL of strong links. The final model
out-performed previous research on the same dataset by 45%.

Committee:

- Yizhou Sun
- Christo Wilson
- Natasha Markuzon (Draper Research Labs)


Andrew W. Fong
Assistant Director for Graduate Admissions and Enrollment

Northeastern University
College of Computer and Information Science
360 Huntington Avenue
202 West Village H
Boston, MA 02115
617-373-8493
a.fong at neu.edu

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