Work log 10/29/16-11/4/16

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I have spent the last week split up between 3 different tasks: Starting to chart the twitter ER diagram, following the O’Reilly Social Media Mining book to continue to learn about harvesting through APIs, and reopening my database systems textbook to remind myself how views work.

After speaking with Charlie last week, we discussed the possibility of using views to select relevant tables from the larger Facebook and Twitter structures to create a model that was easily modifiable and a combination of the two existing models, rather than trying to force the models themselves together into a new, heavily set model.

Work on the Twitter model is coming along, and I hope to be done by the end of this week.

Work Log 10/19/2016-10/27/16

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I spent this week charting out ER diagrams for a Facebook database schema. A lot of this work involved converting DDL statements I found online into a class diagram, and understanding how the classes related to each other. I am now at a point where I understand the entities and their relationships, and the next step is figuring out which of these entities I care about for my project.

I have also been using Mining The Social Web. This book is an overview of data mining popular websites such as Twitter, Facebook, and (interestingly as a social media site), LinkedIn. It even touches on the semantic web and the not-so-popular Google Buzz. Each area is covered with explanations on how to set up programs, a brief introduction to and explanation on the workings of the API, some examples of mining code and a couple of suggestions on how to use it.


I plan to use the data I am learning to harvest through these APIs to test and iteratively hone my data model. I’m currently working on charting out the ER diagram for Twitter, although this is proving trickier than it’s Facebook counterparts because I’ve only been able to find fragments of the model in different places.

Topic Statement

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Deeksha Srinath

Senior Seminar Topic Statement

Advisor: Charlie Peck


My interest in how social media today is influencing our lives influenced my topic. I will be working to design a unified data model for Facebook and Twitter data. I will be doing this in order to be able to query a pool of data that spans multiple social media platforms. This is useful to the scientific process because people interact with different social media sites differently. In designing a unified data model, I will be able to analyse trends across platforms.


Once my data model is established and I have moved my data into it, I am interested in exploring the different scenarios around disordered eating on social media. In a day and age when everyone has access to everyone else’s pictures at the touch of a button, I am curious about what this is doing to body image and body positivity among young women in the US, particularly women of color. Eating disorders in the US are steadily climbing, with thousands of young women losing their lives to disordered eating. Body positivity is also on the rise, with more and more people speaking out about loving their body as is and embracing the beauty in difference.
 I am interested in exploring how to mine trends in the data across platforms. I do not have an ample psychological background to understand all the facets to this part of my project. I will be working with the Psychology department in order to better understand what to look for and how to query my data usefully once it is in a unified format.

Potential Project Ideas

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  1. Connecting a seemingly similar history to a surprisingly variable present

With this project, I would examine how a set of nations (a subset of Scandinavian nations) that are today relatively homogeneous in terms of race and economic capacity have vastly differing attitudes and policies around immigration and integration of immigrants. This interest developed as I was reading about Iceland’s policies around immigration before visiting there, and being struck by it’s vastly open immigration policy. Part of the reason this was so striking to me was it’s proximity to nations that in comparison, are very closed to immigration. I am yet to find the serious Computer Science in this project, but I am hoping that in learning more about the question I am trying to ask, I am helping myself find the Computer Science tools I could use to answer it.


2. Analyzing twitter data to study emotional health as tied to disordered eating

Social media is in our homes, and in our kitchens. This project would be an advent into studying twitter data about eating preferences. With information about healthy eating at everyone’s finger tips, it’s easy to get pulled into the 1234 fad diets that are popular on the interwebs on any given day. Through this project, I would study how patterns in popularity of fad diets affect dietary preferences as projected on twitter. Disordered eating is on the rise in the US, as is veganism. The question I will be trying to ask in this project is whether so called lifestyle changes(such as switching to a vegan lifestyle) have become the ad-hoc way of normlising disordered eating, and whether this phenomenon is discoverable through twitter data.