(Messy) Big Data for Social Good / Pia Ramchandani.

Format:

Book

Thesis/Dissertation

Author/Creator:

Ramchandani, Pia, author.

Contributor:

University of Pennsylvania. Operations, Information and Decisions, degree granting institution.

Language:

English

Subjects (All):

Sociology.

Information science.

Operations, Information and Decisions--Penn dissertations.

Penn dissertations--Operations, Information and Decisions.

Local Subjects:

Sociology.

Information science.

Operations, Information and Decisions--Penn dissertations.

Penn dissertations--Operations, Information and Decisions.

Physical Description:

1 online resource (154 pages)

Contained In:

Dissertations Abstracts International 85-12A.

Place of Publication:

[Philadelphia, Pennsylvania] : University of Pennsylvania, 2022.

Ann Arbor : ProQuest Dissertations & Theses, 2024

Language Note:

English

Summary:

The goal of this work is to develop algorithmic approaches that tackle complex social problems. All three projects included in the dissertation start with large-scale messy datasets in social domains with sensitive nuances that are important for considering when designing algorithmic analyses. Our primary focus areas are human rights abuses in supply chains and counter-sex trafficking investigations. We combine datasets from dozens of sources to provide unique views into these domains. We develop algorithmic methodologies that account for the distinct challenges for each area and share how these contributions can be applied to other domains.

Notes:

Source: Dissertations Abstracts International, Volume: 85-12, Section: A.

Advisors: Bastani, Hamsa Sridhar; Committee members: Netessine, Serguei; Sungu, Alp.

Department: Operations, Information and Decisions.

Ph.D. University of Pennsylvania 2024.

Local Notes:

School code: 0175

ISBN:

9798382830490

Access Restriction:

Restricted for use by site license.