Kate Starbird's Research Group Archive
The following research group descriptions are archived because they are no longer offered, the faculty member is on sabbatical, or the group is taking a break. Please contact the faculty member or an advisor to learn more about these groups.
- Rumor permutations: studying tweets surrounding the Hawaii missile false alarm
- Designing for reflection on social media activity to support resilience to misinformation
- Understanding the human impact of hurricanes through social media
- Understanding conversation strategies on social media: How can we redesign discussion forums?
- Doubt, Disgust & Disinformation: Designing to Support Emotional Reasoning for Networked Societies
- Understanding the Impact of Hurricane Maria on Puerto Ricans through Social Media (En Español)
- 2017–2018 DRG on Online Rumoring, Misinformation and Disinformation during Crisis Events
- Sketching a Field Guide to Contemporary Crisis Information Work
- Tracking Information Flows across Social Media during Disaster Events
- Social Media Use & the 2014 Oso Landslide
- Tracking the Online Spread of Misinformation after Disaster Events
- Increasing Motivation and Participation of Digital Volunteers/Crisis Mappers
- Designing/Developing a Content Curation Web App for Disaster Volunteers
- Understanding Public Information Needs in Crisis Contexts
- Researching at the Intersection of Social Media and Disasters: Tracing the Spread of Misinformation after the 2013 Boston Marathon Bombing
- Collaborative Crisis Curation: Designing a Social Media Processing Tool for Emergency Managers
- Investigating ICT use during Mass Convergence Events
HCDE Asst. Professor Kate Starbird is seeking a small number of students to join an autumn quarter Directed Research Group (DRG — research for credit) looking at rumor permutations — how rumors permute, branch, and otherwise evolve over the course of their lifetime.
Our case study for this DRG are tweets surrounding the Hawaii missile false alarm: At 8:08 am on January 13, 2018, people in the state of Hawaii received a phone alert warning them of an incoming missile. Although (fortunately) this later proved to be a false alarm, for 37 long minutes residents, visitors to Hawaii, and their families across the country (and worldwide) were trying to make sense of the situation (seeking answers to questions such as: Is there a missile? Several missiles? Is/are it/they nuclear? Where did it come from?), and also sending emotional messages in what it was assumed could be their final ‘words’ on Twitter. Initial data exploration has yielded a rumor pertaining to the relationships between the missile alert and North Korea, and this will be the focus of the research.
We are looking for students with a range of different skill sets and abilities, including data science, and qualitative content analysis. Students with programming experience in Python and MySQL are encouraged to apply. Applicants should note that the research will involve in-depth analysis of tweets that were sent during the 37 minutes when people thought there was an incoming missile, and that as a consequence the content may be emotionally-charged.
This research group will be run by HCDE PhD student Tom Wilson and and supervised by HCDE Professor Kate Starbird. If you are interested, please send an email to firstname.lastname@example.org that includes:
- Current CV;
- A brief description of why you interested in the group;
- Any relevant experience;
- What you feel you can bring to the group;
- The number of credits you are seeking.
If you have particular research questions you would be interesting in pursuing you can also note them in your email.
Applications will be reviewed on September 19, 2018, and selected students notified by September 21. Meetings will be held weekly on Monday, Tuesday, or Wednesday and are mandatory for all registered students. The meeting time will be agreed with the selected students. Accepted students should register for 2-3 credits of HCDE 496 / 596 and are expected to conduct 3 hours per week of work outside the classroom for each registered credit.
This directed research group seeks to understand how we can support student reflection on social media trace data related to news and politics. Reflection can be viewed as a kind of thinking that involves stepping outside of a personal situation to acquire deeper understanding and prepare for future action. Our research begins with the premise that supporting reflection on social media data could promote resilience in today’s information environment. In this DRG, we will explore this possibility through designing, participating in, and evaluating activities that allow us to reflect on our own use of social media.
Our approach will be based on a combination of the principles of “participatory design” and "research through design". Researchers in this DRG will be designing tools (e.g. digital systems, visual provocations, classroom activities) to help students reflect on their social media usage and how that might intersect with phenomena like online misinformation and disinformation. To inform our brainstorming and design efforts, researchers will be reflecting on their own social media data and maintaining a record of their experiences as we ideate and try out new things. Creativity, critical thinking, an interest in cultivating self-awareness and exploring the nature of information we find problematic will be key components of our work in this DRG.
This will be a 2-credit hour course for HCDE 496 / 596. The group will meet on Wednesdays from 3:30 to 5:30 p.m. The group will be facilitated by PhD candidate Ahmer Arif and Dr. Kate Starbird. If you are interested in registering, please contact Ahmer at email@example.com.
HCDE Asst. Professor Kate Starbird is seeking students to join an autumn quarter Directed Research Group (research for credit) looking at the human impact of hurricanes through social media. The goal of this research is to use social media trace data to understand how people adapt to the impacts of hurricanes. This is a mixed methods project — using qualitative and quantitative methods to examine social media posts shared in the aftermath of hurricanes in 2017. We hope to develop new “coding schemes” that identify the different kinds of impacts and adaptations that are visible within social media data as well as new methods for exploring social media data to generate those coding schemes.
We are looking for up to three students to do qualitative analysis and up to three students with some data science experience (Python, R, MySQL or Postgres, etc.) to help with analysis. Students from all departments and all levels are welcome to apply.
This DRG would be a great fit for students who:
- have some interest in analysis of large scale social media data sets and/or want to do research to help people in crisis
- can commit 6-9 hours of work per week (2-3 credit hours) for throughout the quarter
We are particularly interested in (but not limited to) applicants who are fully bilingual and/or culturally fluent in contemporary Puerto Rican culture.
We are looking for students to join our winter 2017 quarter Directed Research Group (research for credit) investigating day-to-day conversations on social media platforms like Twitter, Facebook etc. We wish to investigate the following in the context of social media conversations about scientific and political topics:
- How does individual bias impact these conversations?
- What strategies do people use to preserve their self-esteem in such a conversation?
- When do people learn from these conversations? How can we acknowledge such informal learning?
In particular, we are interested in identifying opportunities for redesigning interfaces to facilitate online conversations such that people can overcome their preconceived beliefs. We will conduct a literature review (read and summarize papers) about conversations on social media, create physical chat rooms for mediated discussions, and create low fidelity (paper) prototypes to gather some preliminary user data.
What makes you a suitable candidate?
- Curiosity about human conversations on social media
- Some experience with user research and facilitating user studies
- Prior knowledge (or some understanding) about experimental design
- Passion for designing new user interfaces
- Looking to register for 2-3 credits (i.e. 6-9 hours of weekly work)
The group will be facilitated by Prof. Kate Starbird and PhD student Himanshu Zade. This will be a great opportunity to learn about research through design and user studies. Meeting time is TBD.
In this directed research group, we will think critically about 'fake news' and the human instinct to focus more on protecting one's world-view and less on discerning truth from falsehood. We will learn about how this instinct is being exploited in increasingly sophisticated ways by propagators of online misinformation to promote their ideas and commitments.
We will also explore how cultivating self-awareness around our emotions can help us guide our thinking and behavior around some of these challenges. To do this, we will try out different activities to learn about the challenges we become subject to when we read material we don't agree with. And we will try out activities that might help us step outside of those challenges with an eye toward designing future interventions.
This work will help us understand what we can do in educational and online spaces to address the alarming deterioration of trust and emotional manipulation that is occurring in our public spheres. On a personal level, this work might help you learn about things like: 1) Flavors of online misinformation; and 2) What you can do differently when you engage with information to protect yourself as a citizen.
This will be a 2-credit hour course for HCDE 496 / 596. The group will be facilitated by Ph.D. candidate Ahmer Arif and Dr. Kate Starbird. If you are interested in registering, please contact Ahmer at firstname.lastname@example.org.
HCDE Asst. Professor Kate Starbird is seeking a few students to join a Winter Quarter Directed Research Group (research for credit) looking at the impact of Hurricane Maria on Puerto Ricans. Particularly, we are looking for students who can help with qualitative analysis of Spanish language social media and/or have contextual knowledge of Puerto Rico. Students from all departments and all levels are welcome to apply.
If you are ...
fully bilingual and/or culturally fluent in contemporary Puerto Rican culture
have some interest in qualitative analysis of large scale social media data sets and/or want to do research to help people in crisis
can commit 6 hours of work per week (3 credit hours) for Winter Quarter
please drop a line to email@example.com expressing your interest and relevant background.
Autumn 2017-Spring 2018
We are exploring several research questions about how rumors, misinformation, and disinformation spread online during crisis events (e.g. natural disasters like Hurricane Harvey and terrorist attacks). In related projects, we are looking at 1) how online rumors change over time; 2) the role that journalists and other “professional” media play in spreading and correcting rumors; 3) how intentional disinformation is spread during crisis events.
We need students with various skill sets, including:
motivated and dedicated qualitative researchers with extensive experience studying and/or using social media (for example: Twitter, Reddit, Snapchat)
students with programmatic data science skills (e.g. Python, MySQL, R, Tableau, Gephi)
students with web scraping skills (e.g. using APIs, creating a web scraper for specific URLs)
students with some experience applying machine learning techniques to big data
Meetings times are TBD. This DRG can be taken for 2-3 credits.
If you are interested in applying to participate in this group, please send an email to firstname.lastname@example.org that includes a resume or CV and a written statement or cover letter describing why you would like to be in the group, what you can offer the group, and what you hope to learn by being a part of the group. If you have specific research questions (ours or your own) that you hope to explore within our project, please describe those.
Social media and other information and communication technologies are transforming how people communicate in times of crisis. In this directed research group we will be drawing on recent Human-Computer Interaction literature to make brief sketches (in words and otherwise) of contemporary crisis information workers, what they do, and how they do it. In this way, we will make contemporary scholarship more accessible for practitioners.
Activities will include doing a close reading of selected academic research (about one reading per week). We will then synthesize what we learn in words and images aimed at practitioners.
We are looking for students with a range of different skill sets and interests, including crisis informatics; information design; visual communication; and/or bridging the research-practitioner divide.
Students may use this DRG as an opportunity to learn about contemporary communication in crises and/or develop writing or visual portfolio pieces.
This research group will be led by PhD Candidate Dharma Dailey, with guidance from Assistant Professor Kate Starbird.
Interested students should send Dharma Dailey a resume/CV along with a statement about why you want to be involved and what you can offer to the team. Please mention both relevant past experience and experience you would like to gain. (email@example.com)
This research project examines how social media is used during disaster events such as earthquakes, hurricanes, floods, and acts of terrorism. Expanding upon previous work tracking online rumors, this quarter we will be investigating how information moves through and across social media platforms during disaster events. For example, we may track specific stories or pieces of information as they spread on Twitter, Reddit, Facebook and NextDoor.
Activities this quarter will include: literature review, defining research questions, data collection, and exploratory analysis of social media data. We will collate and summarize existing research in the crisis informatics field—especially studies that look at cross-platform use. From there, we will identify open and important research questions for our group to answer. At the same time, we will work to identify and collect data on emerging events—using existing infrastructure where we have it and building new infrastructure (collection software) where we need it. Once we have data and preliminary research questions, we will conduct exploratory analysis to begin to develop methods of answering our research questions.
We are looking for students with a range of different skill sets and abilities, including software development, data science, and qualitative content analysis. Students who are expert users of Twitter, Reddit and/or other relevant social media sites are encouraged to apply, as are students with programming experience in Python and MySQL.
Interested students should send Professor Kate Starbird a resume/CV along with a statement about why you want to be involved and what you can offer to the team. (firstname.lastname@example.org)
We are examining social media data to better understand how rumors spread after disaster events. Students can see descriptions of this work in past DRG announcements regarding research on the Boston Marathon Bombings. We have created (and continue to develop) an infrastructure to identify emerging crisis events, collect data in real time on those events, find rumors within that data, then "code" and analyze that data. In this large, collaborative project, we are pursuing a diverse set of research questions—e.g. looking at "correction" behaviors, tracking permutations, understanding "sensemaking" behaviors, exploring better models and metaphors to describe rumoring dynamics, etc. Student researchers can contribute by manually coding Twitter data, analyzing that data (qualitatively, quantitatively, and visually), helping to build automatic (machine learning) classifiers to detect misinformation, and writing up reports and papers from those analysis.
We are looking for enthusiastic and dedicated student-researchers with a range of different skill sets and abilities who are willing to commit at least 9 hours (3 credits) per week to the project.
Specific skills for new students in Autumn 2015: we are specifically looking for a small number of students with programming/development experience to help develop our social media data collection framework. For this aspect of the project, ideal students would be interested in user experience, social media, and web applications and would have experience with at least 3 of the following: Django, Django Rest Framework, Angular.js, Node.js, D3.js, PubSub patterns in a web context, and familiarity with Rest APIs.
Spring quarter 2015, the emCOMP lab will be analyzing social media concerning the the 2014 Oso Landslide, a recent mass fatality event in our region. Students will have the opportunity to work individually on analytical deliverables that may lead to publications in the context of an active collaborative research project. We are looking for one or two students to do a qualitative analysis of a key local information resource that made ample use of social media. We are also looking for one or two students with a bit of programming experience who would like to do some quantitive analysis of social media data. Ideal students will have an interest in this event, qualitative analysis of social media, and be self-motivated. This research group will be co-facilitated by two of Kate Starbird's PhD students user researcher Dharma Dailey and software designer John Robinson. If you are interested email us (email@example.com and firstname.lastname@example.org) with a few lines about why your interested and any related experience you have. Previous experience is not required. One weekly meeting and three hours of work per credit hour is required. Minimum 2 credit hours.
We will be examining social media data to better understand how rumors spread after disaster events. Students can see descriptions of this work in past DRG announcements regarding research on the Boston Marathon Bombings. This Autumn Quarter, we will begin to focus on more recent events, including the bombing of MH17, hurricanes in Hawaii, and violence in Iraq.
We will be doing manual coding of Twitter data, big data analysis (qualitative, quantitative, and visual), and building automatic (machine learning) classifiers to detect misinformation. We're looking for students with a range of different skill sets and abilities, including qualitative coders, data scientists, and programmers with some experience using machine learning algorithms. Students who sign up as qualitative coders will have the opportunity to learn data science techniques (e.g. MongoDB, R, Tableau).
Interested students should send Professor Kate Starbird a resume/CV along with a statement about why you want to be involved and what you can offer to the team. (email@example.com)
This research group will be run by HCDE PhD student Dharma Dailey and iSchool PhD candidate Beth Patin, and supervised by HCDE Professor Kate Starbird. If you are interested, please send an email to both Dharma (firstname.lastname@example.org) and Beth (email@example.com) with a brief description of why you interested in the group, any relevant experience, and the number of credits you are seeking. Meetings are mandatory for all registered students. Students should register for 2-3 credits and are expected to conduct 3 hours per week of work outside the classroom for each registered credit.
To develop and deploy a web application to support the collaborative, connected work of digital volunteers
To better understand the phenomenon of digital volunteerism
To better understand how groups collaborate and coordinate online
To publish research on digital volunteerism and online collaboration
database experience (e.g. MySQL, MongoDB, other NoSQL database)
comfortable working as part of a team
help develop coding schemes for our analysis
read and classify 1000s of tweets and web pages
write papers describing our methods, analysis, and findings
make network graphs and other visualizations
implement machine learning algorithms to automatically classify tweets and links
complete statistical analyses on these data
Programming in a scripting language (Python, Ruby or another)
Database programming (MySQL or MongoDB)
Address specific questions about ICT-enabled human behavior during mass participation events, e.g.
Design tools for research and/or real-time analysis of social media interaction during these events, e.g.
Design tools to support the activities of those participating in these events (on-the-ground participants/fans/etc., emergency responders, organizers, digital volunteers, etc.)