Search Results for author: Tim Althoff

Found 13 papers, 3 papers with code

Human-AI Collaboration Enables More Empathic Conversations in Text-based Peer-to-Peer Mental Health Support

no code implementations28 Mar 2022 ASHISH SHARMA, Inna W. Lin, Adam S. Miner, David C. Atkins, Tim Althoff

Advances in artificial intelligence (AI) are enabling systems that augment and collaborate with humans to perform simple, mechanistic tasks like scheduling meetings and grammar-checking text.

Transformer-Based Behavioral Representation Learning Enables Transfer Learning for Mobile Sensing in Small Datasets

no code implementations9 Jul 2021 Mike A. Merrill, Tim Althoff

This architecture combines benefits from CNN and Trans-former architectures to (1) enable better prediction performance by learning directly from raw minute-level sensor data without the need for handcrafted features by up to 0. 33 ROC AUC, and (2) use pretraining to outperform simpler neural models and boosted decision trees with data from as few a dozen participants.

Representation Learning Time Series +1

Towards Facilitating Empathic Conversations in Online Mental Health Support: A Reinforcement Learning Approach

1 code implementation19 Jan 2021 ASHISH SHARMA, Inna W. Lin, Adam S. Miner, David C. Atkins, Tim Althoff

Learning such transformations is challenging and requires a deep understanding of empathy while maintaining conversation quality through text fluency and specificity to the conversational context.

Dialogue Generation Language Modelling +2

Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference

no code implementations21 Sep 2020 Galen Weld, Peter West, Maria Glenski, David Arbour, Ryan Rossi, Tim Althoff

Across 648 experiments and two datasets, we evaluate every commonly used causal inference method and identify their strengths and weaknesses to inform social media researchers seeking to use such methods, and guide future improvements.

Causal Inference

A Computational Approach to Understanding Empathy Expressed in Text-Based Mental Health Support

2 code implementations EMNLP 2020 Ashish Sharma, Adam S. Miner, David C. Atkins, Tim Althoff

We develop a novel unifying theoretically-grounded framework for characterizing the communication of empathy in text-based conversations.

CORAL: COde RepresentAtion Learning with Weakly-Supervised Transformers for Analyzing Data Analysis

no code implementations28 Aug 2020 Ge Zhang, Mike A. Merrill, Yang Liu, Jeffrey Heer, Tim Althoff

Large scale analysis of source code, and in particular scientific source code, holds the promise of better understanding the data science process, identifying analytical best practices, and providing insights to the builders of scientific toolkits.

Representation Learning

Population-Scale Study of Human Needs During the COVID-19 Pandemic: Analysis and Implications

no code implementations17 Aug 2020 Jina Suh, Eric Horvitz, Ryen W. White, Tim Althoff

Most work to date on mitigating the COVID-19 pandemic is focused urgently on biomedicine and epidemiology.


Boba: Authoring and Visualizing Multiverse Analyses

1 code implementation10 Jul 2020 Yang Liu, Alex Kale, Tim Althoff, Jeffrey Heer

Multiverse analysis is an approach to data analysis in which all "reasonable" analytic decisions are evaluated in parallel and interpreted collectively, in order to foster robustness and transparency.

Human-Computer Interaction

The Effect of Moderation on Online Mental Health Conversations

no code implementations19 May 2020 David Wadden, Tal August, Qisheng Li, Tim Althoff

We found that participation in group mental health discussions led to improvements in psychological perspective, and that these improvements were larger in moderated conversations.

Learning Individualized Cardiovascular Responses from Large-scale Wearable Sensors Data

no code implementations4 Dec 2018 Haraldur T. Hallgrímsson, Filip Jankovic, Tim Althoff, Luca Foschini

We consider the problem of modeling cardiovascular responses to physical activity and sleep changes captured by wearable sensors in free living conditions.

Time Series Time Series Forecasting

Detection Bank: An Object Detection Based Video Representation for Multimedia Event Recognition

no code implementations28 May 2014 Tim Althoff, Hyun Oh Song, Trevor Darrell

While low-level image features have proven to be effective representations for visual recognition tasks such as object recognition and scene classification, they are inadequate to capture complex semantic meaning required to solve high-level visual tasks such as multimedia event detection and recognition.

Event Detection Frame +3

How to Ask for a Favor: A Case Study on the Success of Altruistic Requests

no code implementations13 May 2014 Tim Althoff, Cristian Danescu-Niculescu-Mizil, Dan Jurafsky

We present a case study of altruistic requests in an online community where all requests ask for the very same contribution and do not offer anything tangible in return, allowing us to disentangle what is requested from textual and social factors.

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