Most Americans don’t follow political accounts on Twitter and see very little political content on average. However, 55% of Americans are worn out by the amount of political content they see on social media. Why? Political content spikes after key events, even (especially) in seemingly apolitical spaces.
Transfeminine users on Bluesky are subject to a transmisogynistic politics of disposability. This manifests, either directly or indirectly, in intracommunity attacks that often end with the target ostracized from the community. We argue that these attacks are driven by on-platformm, distributed folklore that evolves emergently within the social network, aided by platform affordances.
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Published in MIT CMS/W Thesis, 2017
My undergraduate CMS/W thesis on The Discourse, a Tumblr-based debate around asexual inclusion in the LGBTQIA+ community
Recommended citation: Smith, Alyssa. 2017. “The Discourse: An Online Debate.” Undergraduate Thesis, Cambridge, MA: MIT.
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Published in EMNLP, 2021
An open-source tool to help researchers without computational backgrounds do automated frame detection
Recommended citation: Bhatia, Vibhu, Vidya Prasad Akavoor, Sejin Paik, Lei Guo, Mona Jalal, Alyssa Smith, David Assefa Tofu, et al. 2021. “OpenFraming: Open-Sourced Tool for Computational Framing Analysis of Multilingual Data.” In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations, 242–50. Online and Punta Cana, Dominican Republic: Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.emnlp-demo.28.
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Published in First Monday, 2023
What kinds of stories are told about Britney Spears online during the #FreeBritney movement?
Recommended citation: Smith, Alyssa Hasegawa, Adina Gitomer, and Brooke Foucault Welles. 2023. “You Want a Piece of Me: Britney Spears as a Case Study on the Prominence of Hegemonic Tales and Subversive Stories in Online Media.” First Monday, December. https://doi.org/10.5210/fm.v28i12.13314.
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Published in Bulletin of Applied Transgender Studies, 2025
[ACCEPTED] When it comes to coverage of transgender issues, the interplay between national news outlets and state outlets is more complicated than a simple national-to-local agenda-setting pattern.
Published in PNAS Nexus, 2025
Ever wondered how open triads become transitive? Amplification is one way this happens; we use causal inference and a novel Twitter API hack to empirically prove this.
Recommended citation: Alyssa Hasegawa Smith, Jon Green, Brooke Foucault Welles, David Lazer, Emergent structures of attention on social media are driven by amplification and triad transitivity, PNAS Nexus, 2025;, pgaf106, https://doi.org/10.1093/pnasnexus/pgaf106
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Published in The Journal of Autoethnography, 2025
I draw on my experiences of online bullying via TERFism to make sense of the forces that act in the neoliberal university classroom to preclude transformative learning.
Recommended citation: Smith, Alyssa Hasegawa. 2025. “It Has Been Handled: Hoping for Transformation in the Neoliberal University Setting.“ Journal of Autoethnography, Volume 6 Issue 2. 2025. https://doi.org/10.1525/joae.2025.6.2.243
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Published in Nature Scientific Data, 2026
We combine a higher-order dataset (Bluesky starter packs, which are user-created collections of accounts that other users can then follow en masse with one click) with a dyadic dataset (the Bluesky following network) in a dataset paper. The dataset is available on SOMAR at ICPSR, and we have a preprint of the dataset paper on arXiv.
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Co-presenters: Layla Hashemi, Amy Magnus, and Temitayo Osinubi
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Abstract of Talk: When we pay attention to content online, we generate measurable trace data that provides feedback to content creators, algorithmic/AI actors, and corporations. This information flow governs what topics are discussed, how far content reaches, and what kinds of governance and moderation decisions companies like Meta or Google make to optimize their advertising revenue. The sheer complexity of attention dynamics online can make it difficult to disentangle the impact an individual user or set of users can have on structures of attention within a given online platform. Using theoretical underpinnings from network science, I provide evidence that individual users can durably reshape attention on Twitter (now known as X) through amplification of novel content to their followers (i.e. retweeting/reposting). In this talk, I will begin by introducing some basic network science concepts that are relevant to this research. I will then explain the data and methods I used to analyze following patterns on Twitter/X, walk through the results of my analyses, and discuss the broader implications my research has for the study of social networks, political polarization, and offline consequences of online behavior. Finally, I will conclude by discussing future work that explores information access and quality online from a networked perspective with a focus on algorithmic and AI actors.
Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.