Christoph Riedl Profile
Christoph Riedl

@criedl

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Professor for Information Systems, Northeastern University; Interested in collective intelligence, human-AI teaming & crowdsourcing

Boston, MA
Joined January 2010
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@criedl
Christoph Riedl
5 days
How does social network structure amplify or stifle behavior diffusion? Turns out, complex contagions are more complicated than we thought … (1/7)
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@criedl
Christoph Riedl
5 days
The basic pattern is a tradeoff: reaching more people via random ties or exploit social reinforcement via clustered ties. Paper with Allison Wan @davidlazer @criedl (7/7).
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@criedl
Christoph Riedl
5 days
Clustered networks are even less advantageous when individuals in the network are connected to more people, can influence their neighbors for longer periods of time, or when they require more adopting neighbors to benefit for social reinforcement (6/7).
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@criedl
Christoph Riedl
5 days
While faster spread on clustered networks is possible it does not represent the dominant pattern. Social reinforcement is necessary but insufficient condition for clustered network to diffuse better but faster spread on clustered networks is no test for social reinforcement (5/7).
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@criedl
Christoph Riedl
5 days
Even with strong social reinforcement random networks spread behavior better than clustered networks. Clustered networks outspread random networks in only a small region of the space we model and mostly only when behavior is near deterministic (4/7)
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@criedl
Christoph Riedl
5 days
We develop a novel model of behavior diffusion with tunable probabilistic adoption and social reinforcement parameters that contains many prior diffusion models as special cases (3/7)
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@criedl
Christoph Riedl
5 days
Complex contagion theory suggests socially reinforced behaviors spread more on clustered networks. But when spread is modeled with realistic probabilistic adoption, in most cases behaviors spread equally-if not better-on random networks (2/7).
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@criedl
Christoph Riedl
9 days
RT @nikhil07prakash: We constructed CausalToM, a dataset suitable for causal analysis, that consists of simple stories where two characters….
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@criedl
Christoph Riedl
9 days
Join us for our “Human-AI Teaming for People and Planet,” workshop at the CI'25 in San Diego
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@criedl
Christoph Riedl
19 days
RT @nikhil07prakash: How do language models track mental states of each character in a story, often referred to as Theory of Mind?. Our rec….
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@criedl
Christoph Riedl
1 month
RT @safe_paper: Language Models use Lookbacks to Track Beliefs. Nikhil Prakash (@nikhil07prakash), @NatalieShapira, Arnab Sen Sharma (@arna….
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@criedl
Christoph Riedl
3 months
RT @NUnetsi: 🚀 Now accepting applications for the new MS in Complex Network Analysis at Northeastern! Study real-world systems—social, fin….
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@criedl
Christoph Riedl
3 months
RT @VminVsky: New paper: Language models have “universal” concept representation – but can they capture cultural nuance? 🌏. If someone from….
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@criedl
Christoph Riedl
4 months
RT @davidbau: Why is interpretability the key to dominance in AI?. Not winning the scaling race, or banning China. Our answer to OSTP/NSF,….
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@criedl
Christoph Riedl
5 months
RT @nberpubs: Because of missed opportunities and regrettable purchases, differentiated product choices can have large welfare costs, which….
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@criedl
Christoph Riedl
5 months
RT @WFUEconomics: 📢 Join us for the first Spring 2025 VIDE seminar!.📅 Feb 5 | 11 AM ET.🎙 Joel Waldfogel (Minnesota) on information & welfar….
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@criedl
Christoph Riedl
6 months
RT @alz_zyd_: Here's a cool paper estimating a model of demand for buying and playing videogames, using Steam playtime data. tl;dr:. - Mone….
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@criedl
Christoph Riedl
6 months
RT @ReimersImke: @alz_zyd_ But we go further. We treat the deviations from proportionality as different marginal utilities of hours across….
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@criedl
Christoph Riedl
6 months
RT @JWaldfogel: With differentiated products and heterogeneous consumers, it may be hard for choices to deliver maximal welfare. We might r….
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@criedl
Christoph Riedl
6 months
AI has effect on worker compensation not only for supply-demand reasons but also psychological ones: people reduce worker compensation just for using AI
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