Public Sentiment of Canceled Celebrities

This summer, Professor Ho and I worked on a behavioral economics project examining the effectiveness of various apology types on the ability of celebrities and public figures to return to society after being “canceled.”

 

For our work, we looked first to well publicized celebrity apologies. We collected a sample of celebrity apologies based on two online databases: a New York Times dataset of celebrities who were publicly reprimanded during the #metoo movement and a dataset compiled by the online apology blog SorryWatch who noted and analyzed a number of celebrity apologies in the recent decades, culminating in over 200 apologies. We then used Amazon Mturk to categorize and assess the effectiveness of these apologies through a survey we constructed.

 

We additionally worked with academic access from Twitter to download databases of tweets referencing the celebrities within our dataset. These databases of tweets consist of a sample of tweets from six distinct periods of interest: 

  1.  Random collection of tweets from the year prior to the cancellation
  2. A database of tweets directly before the news of the cancellable event was published
  3. A database of tweets directly after the news of the cancellable event was published
  4. A database of tweets directly before the celebrity apologized
  5. A database of tweets directly after the celebrity apologized
  6. Random collection of tweets from the year following the issuing of the apology

A screenshot of some of the code used to create our tweet databases.

We then used the open source program VADERsentiment to analyze the overall sentiment of the tweets contained in our databases to quantify how public sentiment towards the celebrity changed over time. Our initial results are promising and in line with some of our initial hypotheses, and I hope that our continued collaboration on this project will yield interesting results. 

 

This image depicts an example output of our sentiment analysis of the tweet dataset for Kevin Spacey.

Resilience Stories: Investigating Science-Based Strategies to Effectively Manage Stress and Adversity

This summer, we worked with Professor Michele Tugade to research evidence-based strategies for managing stress and strengthening resilience. Through exploring the current literature, participating in workshops, and hearing personal experiences, we were able to identify key markers of resilience and start brainstorming ways that we could teach it effectively. 

Our first task was to investigate the current literature on resilience and develop summaries of their theories and findings. This work was the foundation for our entire project as we began creating infographics, interview questions, and eventually a website. We used platforms such as The Greater Good and Character Lab to identify approaches to common themes of resilience such as self-compassion, gratitude, growth mindset, and goal agility.

We created infographics on the Self-Compassion Cycle, Tender & Fierce Self-Compassion (Dr. Kristin Neff), and Emotional Nuance. We also developed interview questions for future work, highlighting the different perspectives/narratives of resilience and the power of storytelling.

Self-Compassion Infographics and Series

Next, we decided to develop a website where the research and resources could be shared. When designing the website, we wanted to identify both the strengths and limitations of what was currently offered. First, we noticed that a majority of the resources were inaccessible due to their high prices and time-consuming workshops. Additionally, we found that current research related to resilience and PTG lacked consideration of its theoretical applications in different cultural, social, and individual contexts. With this in mind, our goals were to address these limitations, make resources more accessible, and account for different perspectives.

Resilience Stories Website Homepage

Resilience Stories Website — Podcasts

This project has shown us the power of individual resilience and the importance of implementing these strategies whenever possible in our daily lives. The future directions of this project include creating a focus group for the website, conducting interviews, and submitting a research proposal to the APA.

Judicial Research: The Identities and Experiences of State Court Judges

This summer, we worked with Professor Taneisha Means researching the pre-bench lives of state court judges across the United States. We received a valuable introduction to concepts of law and judicial politics. 

For our first collective project, we researched background characteristics such as political, educational, and socio-economic background to determine how the pre-bench lives of state court judges differ across racial lines. Our work entailed analyzing transcriptions from 96 interviews with state court judges and survey data among approximately 600 judges to understand judicial diversity in state courts.

Ben Fikhman ’23 and Simon LaClair ’24 organizing data gathered from interviews with judges

We each then worked on a different paper co-authored with Professor Means. Ben researched judges’ experiences with and perceptions of race-based, gender-based, and sexuality-based disqualification requests from litigants who sometimes question the impartiality of minority judges. Simon worked on evaluating the mental health support, stress, career satisfaction, and general well-being of state court judges. We developed our data analysis skills, our understanding of how to craft scholarly articles, and our knowledge of the topics we studied.

Our experience with this project emphasizes the scholarly importance of state court judges, who hold tremendous influence over citizens’ lives. Despite this reality, we have come to realize research on state court judges is limited and more is needed. We are thrilled to be a part of Professor Means’ exploration into the politics of state judges and courts.

A spreadsheet keeping track of progress with interviewing and transcribing

By enhancing our knowledge of judicial terminology, discovering new ways to organize data, and learning about general research methodology, we dipped our feet into the world of law in a more substantive way than we first anticipated. Beyond the systematic analysis of judges, this project helped us understand the human perspective behind the state judiciary – the personal stories among hundreds of judges that underlie the complexity of judicial politics and the justice system.

Wage, Wealth, Employment, and Immigrants (Empirical)

This summer I worked with Professor Argudo and four other interns to continue research on the wage and wealth gaps between people born in the United States (henceforth called natives), authorized immigrants, and unauthorized immigrants. Previous research on this topic has documented wage disparities between all three nativity groups and wealth disparities between natives and immigrants. Our research is novel in its distinction between types of immigrants when surveying wealth gaps, as well as the inclusion of asset holdings. 

 Our work this summer built on Professor Argudo’s 2021 Ford Scholar project. We continued to use Survey of Income and Program Participation (SIPP) data, which changed considerably during the time period we examined. Since we did not finish matching the variables we needed last summer, the team and I began homogenizing the remaining relevant variables such as race, occupation, and industry from 1996 to 2020. This left us with a nationwide dataset of individuals that could be tracked over multiple months and years.

Sample of homogenization code for industries

 The initial stages of our analysis focused on using the homogenized data to replicate figures from previous papers that compared immigrants and natives to confirm our data was valid. Once confirmed, we distinguished between authorized and unauthorized immigrants using  George J. Borjas’s methodology, and split the data into workers of different education levels. The final days of the project were spent starting a paper to summarize our findings and introduce our research, along with creating graphs on wealth holdings by nativity group. 

Comparison between different datasets of percent of unauthorized immigrants at each education level in the population.

This project has not only sharpened my ability to consider economic scenarios in real life, but it has given me skills in Python and data analysis that are indispensable in research and data science. 



Product Quality and Consumer Response: Using Evidence from the U.S. Airline Industry

This summer, I worked with Professor Ge and Jiebei Luo, and my peer Madhav Jha on the U.S. Airline project. Specifically, we aim to discuss the product quality and consumer response using the tweets that we scraped from the Twitter API. In case of the airline industry, the number of airlines in a competitive market is low due to scale economies. Some airlines maintained their monopoly status on specific routes, and their failure to improve service quality (worsening delays) has raised nation-wise concerns and increased consumer dissatisfaction. As social media platforms (e.g., Twitter in our case) provide large amount of text data, we are able to locate tweets directed at a specific airline through mentions (@). See 1-1 below for sample tweets. Considering the short span of the program and the exploratory nature of our project, we limited our data coverage and focused on two chosen airlines, Alaska Air and JetBlue (Delta and Southwest Air in Madhav’s case), on a sample date pre-covid (Nov 12, 2019).

1-1 Sample tweets

To retrieve historical tweets, we utilized the Twitter API, a platform that allows you to find and retrieve, engage with, or create a variety of different resources including the following: user ID, time created, text, and more. 1-2 shows an example of the tweets we pulled. Since many tweets contains URLs, digits, and other things that might disrupt the sentiment analysis, we preprocessed the tweets to trim them and make them ready for future steps.

@JetBlue 2019-11-12 23:12:31+00:00 @JetBlue So your response is basically, “Suck it up, we’re giving you a flight credit later so who cares that you waste a day of your life and have to pay your own money to eat?” 1194392560371994626
@JetBlue 2019-11-12 23:12:11+00:00 @JetBlue We have and at 10am they had the phone and now nobody knows anything 1194392474992676864
@JetBlue 2019-11-12 23:08:53+00:00 .@JetBlue just sent a second email to Mosaic members explaining the fare family changes from this morning (https://t.co/zLHmhCJzzi) and their impact on the elites in the TrueBlue program. It is a good chart. I have no idea why it wasn’t the first message sent 10 hours ago. #PaxEx https://t.co/c0ycO8K5NQ 1194391642976817153
@JetBlue 2019-11-12 23:08:08+00:00 @JetBlue I was scheduled for 2 pm. Now scheduled for 9:15. $250 was thrown out but no guarantee that we will leave tonight. 1194391457551044611

@JetBlue

2019-11-12 23:07:59+00:00 @sbbiscuit @JetBlue Interesting that’s kind of what I thought was happening. I mean I don’t know if blue plus really saved with the bags anyway but still 1194391417549918208

1-2 Retrieved Tweets

The purpose of preprocessing is to get rid of any unwanted/irrelevant text elements. To conduct sentiment analysis, we used two different toolkits, TextBlob and Vander, in order to compare between results. However, computer programs have problems recognizing things like sarcasm and irony, negation, jokes, and exaggeration – things that are easy for a human to sense and identify. Failure to recognize these things can skew the results. And since some tweets contains multiple mentions, even when the overall sentiment is negative, the sentiment toward a specific airline is not necessarily negative. Therefore, after putting the texts through automated analyzing programs, we manually identified each of the tweets. See 1-3 for an example when sarcasm cannot be detected by the programs.

Text Preprocessed Polarity Sentiment_Type_TextBlob scores compound Sentiment_Type_Vader Manually
@JetBlue Very happy to hear. Regardless, I’ll be sure to avoid the Blue Basic fares like the plague.

 

jetblue happy hear regardless ill sure avoid blue basic fare like plague 0.16 POSITIVE {‘neg’: 0.244, ‘neu’: 0.341, ‘pos’: 0.415, ‘compound’: 0.5423} 0.5423 POSITIVE NEGATIVE

1-3

Our next step would be to create visualizations to help illustrate our analysis. This summer has been really rewarding as I had zero experience in scraping data, preprocessing data, and text/sentiment analysis prior to this project. Exploring new areas is always exciting and learning about the airline industry is so relevant to our day-to-day life. Even though the research has just started, and we still have a long way to go before we draw any conclusion, being able to start from scratch and building new skills and knowledge on every step of the way is beyond precious. I would like to thank Professor Ge and Jiebei for this wonderful opportunity and experience.

Haiyi (Olivia) Xiao

China Reimagined: An Alternative History in Nine Parts

This summer, I worked with Professor Michael Walsh on his project “China Reimagined: An Alternative History in Nine Parts.” While refining his first-year writing seminar “China Reimagined,” the project will also be expanded into a book that provides alternative perspectives of Chinese history than the more traditional chronologies.

The project is inspired by 洛書 (LuoShu), an ancient mystical chart that appeared from the Luo River in central China. 

the chart of 洛書 (LuoShu) after the Song dynasty 

Our primary task was to explore the concept of “China” through 9 themes, beginning with “territory” 國, which concentrates broadly on Chinese cosmology, and ending with “people”民.

The challenge of the project is that it’s impossible to give a comprehensive conclusion of what China is and who ‘counts’ as Chinese. We worked together to figure out the most appropriate nine themes for the book project and the appropriate Chinese and English titles for each topic. I also researched the etymology of relevant Chinese terms.

Besides tracing the history of LuoShu, I mainly worked to find primary and secondary resources in Chinese both in the library and online. Professor Walsh gave me much freedom to explore these topics and I found myself dwelling on some topics like “territory” and “city” while spending less time on others. I then translated, summarized, and annotated  the information I found.


 Yu Ji Tu (禹跡圖), 1136

Book of Diverse Crafts (考工記), the image of the King’s city (王城圖)

For me, it was also about learning the process of exploring academic research and about research material selection. Additionally, translating the texts was a surprisingly helpful way of learning. I found myself knowing a lot more than merely “reading through the words.” It almost feels like the 8 weeks of research just started yesterday. I want to thank Professor Walsh for making this a wonderful experience. 

 

Economic Consequences of Childhood Exposure to Environmental Toxins

This summer, we worked with Professor Frye and Professor Kagy to research the economic consequences of childhood exposure to environmental toxins. We primarily focused on evaluating whether early exposure to lead would cause differences in intergenerational mobility, occupational rank, and total years of schooling. 

The project involved constructing a highly intricate data set that pulled together information on people and towns in the northeast, where the integration of central water systems was prevalent around the turn of the twentieth century and the use of lead and non-lead materials for the municipal pipes varied. We used IPUMS to collect census data for the late nineteenth and early twentieth centuries, the Census Linking Project to probabilistically match people across censuses, the Census Place Project to identify where these people lived, and two books that organized information on cities’ water systems and water chemistry. 

Due to the large sizes of the data, we relied on Amazon’s Web Server to run code in RStudio that could compile and build our data set. Our final data set allowed us to identify children in the Northeast as living in either lead or non-lead cities, and then track this cohort overtime to evaluate their outcomes in adulthood.

Exploratory data analysis, involving graphs, maps and summary statistics tables, shows early implications that exposure to lead in childhood does have negative long-term economic consequences. For example, the average income in 1940 for a child exposed to lead in 1900 was $6062 less than the average for a child who was not exposed to lead via city service pipes.

Figure 1: This map visualizes where lead pipes were located in Maine, Rhode Island, New Hampshire, Massachusetts., Pennsylvania and New York.

This project also sparked an interest in current-day exposure to toxins and made us more cautious about what we may be consuming in our day-to-day lives. Moreover, this project was a very rewarding experience that enabled us to greatly improve our coding skills and collaborate with our professors, who offered deep insights into working in research. We are grateful that we had this opportunity to learn first-hand about economic research and be part of an exciting and innovative project.

 

“How do we honor our stories enough to quiet the voices inside [that tell us our voices don’t matter]?” -Dr. Laura Biagi

This summer Professor Erin McCloskey and I, Marissa Desir ’25, learned about rehumanization through storytelling. Done remotely, we jumped eagerly into this budding research project, fascinated yet inquisitive of each concept. The intention was to recognize the impact of exchanging personal narratives as a transformative pedagogical approach and its role in strengthening relationships within the triad of home, school, and community through its ability to reconstruct barriers surrounding social identities.

Furthermore, the inclusion of this method within classrooms involving those incarcerated (or formerly), and local university students. Our time spent emphasized the value of self-authorship as a form of resistance against dominant power structures and as, a tool for forming authentic and constructivist learning environments with students at the core of the curriculum.

From the beginning, there was a need to gather research from all forms of media such as books, peer-reviewed articles, TedTalks, and documentaries to represent the multimodal storytelling that would take place. We then developed an annotated bibliography that would factor in creating an applicable framework that could be sent to the Institutional Review Board. As the project was in its early stages, we were able to discuss how to create positions of strength within the classroom for different types of narratives. While also discussing the possible drawbacks of confining this approach to an academic setting and addressing the dangers of exchanging traumatic stories. Ultimately, this call to exchange allows for reinterpretations and inclusive solutions that prompt community engagement, activism, and identity-making. 

As Professor McCloskey continues her work, I thank her for allowing me to contribute over the summer and acquaint myself with a topic I now harbor a passion for. 

Wage, Wealth, Employment, and Immigrant

My work over the Ford period focused on understanding the mechanism described in a paper by Chaumont and Shi, 2022, by replicating it using python. Initially, it was challenging for me to sufficiently understand Chaumont and Shi’s work without much prior knowledge of the field of job transitioning and wealth study. With the aid of Professor Argudo who patiently answered all my questions over several meetings, I grasped enough to start my own replication. The process was still demanding, but through trials and errors, I have acquired similar results using the method of Value function iteration (VFI). I am familiar with VFI thanks to ECON 304 with Professor Argudo from the previous semester, but tackling such a task with so much independence as I have in the Ford program was something I have never done before. For me, It was a pleasure to receive this opportunity through Ford to assist in professor Argudo’s research and challenge myself outside of my comfort zone.

 

 

Preparing the Translated First Volume of Oviedo’s General and Natural History for Publication

This summer, I worked with Professor Paravisini-Gerbert and Professor Aronna to prepare a translation of the first volume of Gonzalo de Oviedo’s General and Natural History of the Indies and Ocean Sea for publication. As the royal historian for Spain in the early 1500s, Oviedo produced the first comprehensive history of Spanish America. Covering local flora and fauna, indigenous practices, political scandals, brutal Spanish colonization, and much more, this account offers a vibrant and information dense view into this violent, fascinating, and formative period of American history, and I feel beyond lucky to have helped with the first ever complete translation of this work.

Illustrations from the 1851 edition of Oviedo’s General and Natural History of the Indies.

One of my responsibilities this summer included assisting with proofreading and editing the translation. This project was a collaborative effort, with many different students translating different chapters; this meant that despite each translators’ high quality work, sometimes the same word would be translated several different ways across chapters. We cross-referenced each chapter to the original text while editing, ensuring the final product would be a faithful and cohesive adaptation. 

A view of the editing process–– we were changing the translation of “oidor” from “judge” to the more accurate “high court judge.”

Once the chapters were edited and triple checked, I would help upload them to Scalar. Scalar is a website that flows like a book, and my duties included adding content, styling the website, and working out any bugs along the way. Through this process I was exposed to a wide variety of art from early Spanish America, learned the basics of CSS, and gained experience building a website.

Two pages on a website. the first displays a hand-painted map of Puerto Rico from 1602, with the text "Book XVI" written in a quill-like font. Below that is a brown button that reads "Begin with 'Book XVI: Preface'." The second page displays this preface in black text on a white backdrop, with a lower opacity version of the map on each side.

An example of how the books look on Scalar.

However, above all, I was able to catch a glimpse of what life was like in early Spanish America, complete with details I would have never otherwise imagined. Sometimes horrifying, sometimes snarky, and always interesting, this Historia is a treasure trove of information and I am grateful to have played a role in bringing it to a wider audience.