Papers by Anthony Hills

3 papers
Exciting Mood Changes: A Time-aware Hierarchical Transformer for Change Detection Modelling (2024.findings-acl)

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Challenge: Existing work on temporally sensitive tasks focuses on predicting mood changes . however, there is little attention given to the importance of longitudinal language modelling .
Approach: They propose a Hawkes process-inspired transformation layer to model the influence of time on users’ posts, capturing both their immediate and historical dynamics.
Outcome: The proposed model outperforms existing models on two existing datasets and shows clear performance gains.
Identifying Moments of Change from Longitudinal User Text (2022.acl-long)

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Challenge: Identifying changes in individuals’ behaviour and mood via shared content is gaining importance given the global increase in mental health disorders and the limited access to support services.
Approach: They propose a task of identifying moments of change in individuals on the basis of their shared content online.
Outcome: The proposed task is based on 500 manually annotated user timelines and shows that it performs best through context aware sequential modelling.
Creation and evaluation of timelines for longitudinal user posts (2023.eacl-main)

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Challenge: Existing methods for segmenting user posts into timelines improve quality and cost of manual annotation.
Approach: They propose a set of methods for segmenting longitudinal user posts into timelines likely to contain interesting moments of change in a user’s behaviour based on their online posting activity.
Outcome: The proposed framework is able to evaluate two different social media datasets and compares with existing models.

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