Event Title

Summer Undergraduate Research Fellowship Panel

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Document Type

Presentation

Start Date

13-10-2020 4:00 PM

End Date

13-10-2020 5:00 PM

Description

Carmen Huang - Emotions in Film Media

My study examined the emotions displayed by characters in popular race-specific films targeted for children, as well as how people interpret the emotions shown. To assess whether characters of different races (Black, White, Asian, Hispanic/Latino) portrayed different emotions, I coded emotion portrayals from 20 films, five films from each race. From these codings, I examined whether the emotions varied by race, as well as whether the emotions were consistent with cultural values. To assess how people interpreted the emotions, I recruited 40 participants and conducted Zoom calls with them. Participants watched eight film clips (two clips from each race) and answered questions regarding how they felt and how the characters felt. By doing so, I examined whether participants related to these emotions and whether they mirrored the characters’ emotions. Racial variations in emotion portrayals are important because people learn about emotions through media, therefore understanding differences in emotion portrayals may have implications for regulating emotions and better understanding oneself.

Arthur Jones -Machine Learning in Finance: Using Neural Networks to Predict Stock Returns

There have been multiple attempts to predict stock returns using machine learning, which have largely used historical time series data on share prices to make these predictions. Those attempts create networks which only work on one firm's data, and cannot be applied generally. This study uses a neural network to predict stock returns based on financial and economic data. The method that is employed here predicts whether a given stock will beat the S&P 500 index over a future time period. This method has reached prediction accuracy of 64.5% to date. A method which makes consistently accurate predictions helps to identify additional factors that determine a firm’s value beyond what is generally accepted in the literature.

Yuki Nagase - The Problem With The Woman Composer Question

When thinking of the faces of classical music, there are likely very few for whom a woman’s name would be immediate. As the discourse surrounding the lack of representation of women composers in Western classical music becomes more and more vocal, a question that often arises in an effort to illuminate the reasons for this discrepancy is “where are the great women composers?”, or more specifically, “why are there no great women composers?” This presentation will discuss why this question - despite its facade of advocacy - and the approach it suggests are misguided and inherently rooted in patriarchy, and how that has consequences beyond the scope of Western classical music.

Speaker Bio

The three presenters are undergraduate students at University of the Pacific. Carmen Huang is majoring in Psychology; Arthur Jones in Business Administration; and Yuki Nagase in Music Performance. Research for these projects was conducted as part of the Summer Undergraduate Research Fellowship.

Comments

(SURF) Summer Undergraduate Research Fellowships

The Summer Undergraduate Research Fellowship (SURF) supports faculty-mentored undergraduate research during the summer. This is an opportunity for students to work with a faculty mentor on a research topic relevant to their interests and educational goals during the summer. The expectation is that students will devote 8-10 weeks of full-time effort to the project. Whether you are a seasoned researcher or this is your first undergraduate research project – SURF is a great chance to expand your educational experience.

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Oct 13th, 4:00 PM Oct 13th, 5:00 PM

Summer Undergraduate Research Fellowship Panel

Carmen Huang - Emotions in Film Media

My study examined the emotions displayed by characters in popular race-specific films targeted for children, as well as how people interpret the emotions shown. To assess whether characters of different races (Black, White, Asian, Hispanic/Latino) portrayed different emotions, I coded emotion portrayals from 20 films, five films from each race. From these codings, I examined whether the emotions varied by race, as well as whether the emotions were consistent with cultural values. To assess how people interpreted the emotions, I recruited 40 participants and conducted Zoom calls with them. Participants watched eight film clips (two clips from each race) and answered questions regarding how they felt and how the characters felt. By doing so, I examined whether participants related to these emotions and whether they mirrored the characters’ emotions. Racial variations in emotion portrayals are important because people learn about emotions through media, therefore understanding differences in emotion portrayals may have implications for regulating emotions and better understanding oneself.

Arthur Jones -Machine Learning in Finance: Using Neural Networks to Predict Stock Returns

There have been multiple attempts to predict stock returns using machine learning, which have largely used historical time series data on share prices to make these predictions. Those attempts create networks which only work on one firm's data, and cannot be applied generally. This study uses a neural network to predict stock returns based on financial and economic data. The method that is employed here predicts whether a given stock will beat the S&P 500 index over a future time period. This method has reached prediction accuracy of 64.5% to date. A method which makes consistently accurate predictions helps to identify additional factors that determine a firm’s value beyond what is generally accepted in the literature.

Yuki Nagase - The Problem With The Woman Composer Question

When thinking of the faces of classical music, there are likely very few for whom a woman’s name would be immediate. As the discourse surrounding the lack of representation of women composers in Western classical music becomes more and more vocal, a question that often arises in an effort to illuminate the reasons for this discrepancy is “where are the great women composers?”, or more specifically, “why are there no great women composers?” This presentation will discuss why this question - despite its facade of advocacy - and the approach it suggests are misguided and inherently rooted in patriarchy, and how that has consequences beyond the scope of Western classical music.