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Analyzing User Comments On Youtube Coding Tutorial Videos, Elizabeth Heidi Poche Jan 2017

Analyzing User Comments On Youtube Coding Tutorial Videos, Elizabeth Heidi Poche

LSU Master's Theses

Video coding tutorials enable expert and novice programmers to visually observe real developers write, debug, and execute code. Previous research in this domain has focused on helping programmers find relevant content in coding tutorial videos as well as understanding the motivation and needs of content creators. In this thesis, we focus on the link connecting programmers creating coding videos with their audience. More specifically, we analyze user comments on YouTube coding tutorial videos. Our main objective is to help content creators to effectively understand the needs and concerns of their viewers, thus respond faster to these concerns and deliver higher-quality …


Interactive Web-Based Visualization Of Atomic Position-Time Series Data, Simron Thapa Jan 2017

Interactive Web-Based Visualization Of Atomic Position-Time Series Data, Simron Thapa

LSU Master's Theses

Extracting and interpreting the information contained in large sets of time-varying three dimensional positional data for the constituent atoms of simulated material system is a challenging task. This thesis work reports our initial implementation of a web-based visualization system and its use-case study. The system allows the users to perform the desired visualization task on a web browser for the position-time series data extracted from the local or remote hosts. It involves a pre-processing step for data reduction, which involves skipping uninteresting parts of the data uniformly (at full atomic configuration level) or non-uniformly (at atomic species level or individual …


A Study On User Demographic Inference Via Ratings In Recommender Systems, Changbin Li Jan 2017

A Study On User Demographic Inference Via Ratings In Recommender Systems, Changbin Li

LSU Master's Theses

Everyday, millions of people interact with online services that adopt recommender systems, such as personalized movie, news and product recommendation services. Research has shown that the demographic attributes of users such as age and gender can further improve the performance of recommender systems and can be very useful for many other applications such as marketing and social studies. However, users do not always provide those details in their online profiles due to privacy concern. On the other hand, user interactions such as ratings in recommender systems may provide an alternative way to infer demographic information. Most existing approaches can infer …