Stance detection on social media: State of the art and trends
Stance detection on social media is an emerging opinion mining paradigm for various social
and political applications in which sentiment analysis may be sub-optimal. There has been a …
and political applications in which sentiment analysis may be sub-optimal. There has been a …
[HTML][HTML] Empirical evaluation of pre-trained transformers for human-level NLP: The role of sample size and dimensionality
In human-level NLP tasks, such as predicting mental health, personality, or demographics,
the number of observations is often smaller than the standard 768+ hidden state sizes of …
the number of observations is often smaller than the standard 768+ hidden state sizes of …
Human language modeling
Natural language is generated by people, yet traditional language modeling views words or
documents as if generated independently. Here, we propose human language modeling …
documents as if generated independently. Here, we propose human language modeling …
MeLT: Message-level transformer with masked document representations as pre-training for stance detection
Much of natural language processing is focused on leveraging large capacity language
models, typically trained over single messages with a task of predicting one or more tokens …
models, typically trained over single messages with a task of predicting one or more tokens …
[HTML][HTML] Replicable semi-supervised approaches to state-of-the-art stance detection of tweets
Stance is defined as the expression of a speaker's standpoint towards a given target or
entity. To date, the most reliable method for measuring stance is opinion surveys. However …
entity. To date, the most reliable method for measuring stance is opinion surveys. However …
Language as a fingerprint: Self-supervised learning of user encodings using transformers
The way we talk carries information about who we are. Demographics, personality, clinical
conditions, political preferences influence what we speak about and how, suggesting that …
conditions, political preferences influence what we speak about and how, suggesting that …
The subtle language of exclusion: Identifying the Toxic Speech of Trans-exclusionary Radical Feminists
Toxic language can take many forms, from explicit hate speech to more subtle
microaggressions. Within this space, models identifying transphobic language have largely …
microaggressions. Within this space, models identifying transphobic language have largely …
[PDF][PDF] Characterizing social spambots by their human traits
Social spambots, an emerging class of spammers attempting to emulate people, are difficult
for both human annotators and classic bot detection techniques to reliably distinguish from …
for both human annotators and classic bot detection techniques to reliably distinguish from …
Large human language models: A need and the challenges
As research in human-centered NLP advances, there is a growing recognition of the
importance of incorporating human and social factors into NLP models. At the same time …
importance of incorporating human and social factors into NLP models. At the same time …
LMSOC: An approach for socially sensitive pretraining
While large-scale pretrained language models have been shown to learn effective linguistic
representations for many NLP tasks, there remain many real-world contextual aspects of …
representations for many NLP tasks, there remain many real-world contextual aspects of …