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Found 37 papers, 24 papers with code
Better than Average: Paired Evaluation of NLP systems
Evaluation in NLP is usually done by comparing the scores of competing systems independently averaged over a common set of test instances.
Laughing Heads: Can Transformers Detect What Makes a Sentence Funny?
We make progress in both respects by training and analyzing transformer-based humor recognition models on a recently introduced dataset consisting of minimal pairs of aligned sentences, one serious, the other humorous.
Low-rank Subspaces for Unsupervised Entity Linking
Geometrically speaking, when representing entities as vectors via some given embedding, the gold entities tend to lie in a low-rank subspace of the full embedding space.
Recursive input and state estimation: A general framework for learning from time series with missing data
Time series with missing data are signals encountered in important settings for machine learning.
Broccoli: Sprinkling Lightweight Vocabulary Learning into Everyday Information Diets
Thus, by seeing words in context, the user can assimilate new vocabulary without much conscious effort.
Are Anti-Feminist Communities Gateways to the Far Right? Evidence from Reddit and YouTube
Our results suggest that there is a large overlap between the user bases of the Alt-right and of the Manosphere and that members of the Manosphere have a bigger chance to engage with far right content than carefully chosen counterparts.
Computers and Society
Volunteer contributions to Wikipedia increased during COVID-19 mobility restrictions
Wikipedia, the largest encyclopedia ever created, is a global initiative driven by volunteer contributions.
Computers and Society
Formation of Social Ties Influences Food Choice: A Campus-Wide Longitudinal Study
To estimate causal effects from the passively observed log data, we control confounds in a matched quasi-experimental design: we identify focal users who at first do not have any regular eating partners but then start eating with a fixed partner regularly, and we match focal users into comparison pairs such that paired users are nearly identical with respect to covariates measured before acquiring the partner, where the two focal users' new eating partners diverge in the healthiness of their respective food choice.
YouNiverse: Large-Scale Channel and Video Metadata from English-Speaking YouTube
YouTube plays a key role in entertaining and informing people around the globe.
Time Series
Social and Information Networks
Computers and Society
Node Attribute Completion in Knowledge Graphs with Multi-Relational Propagation
The existing literature on knowledge graph completion mostly focuses on the link prediction task.
KLearn: Background Knowledge Inference from Summarization Data
The goal of text summarization is to compress documents to the relevant information while excluding background information already known to the receiver.
Crosslingual Topic Modeling with WikiPDA
We present Wikipedia-based Polyglot Dirichlet Allocation (WikiPDA), a crosslingual topic model that learns to represent Wikipedia articles written in any language as distributions over a common set of language-independent topics.
Adoption of Twitter's New Length Limit: Is 280 the New 140?
The prevalence of tweets around 140 characters before the switch in a given language is strongly correlated with the prevalence of tweets around 280 characters after the switch in the same language, and very long tweets are vastly more popular on Web clients than on mobile clients.
Experts and authorities receive disproportionate attention on Twitter during the COVID-19 crisis
Timely access to accurate information is crucial during the COVID-19 pandemic.
Social and Information Networks
Calibration of Google Trends Time Series
In the offline preprocessing phase, an "anchor bank" is constructed, a set of queries spanning the full spectrum of popularity, all calibrated against a common reference query by carefully chaining together multiple Google Trends requests.
A Ladder of Causal Distances
Causal discovery, the task of automatically constructing a causal model from data, is of major significance across the sciences.
On the Limitations of Cross-lingual Encoders as Exposed by Reference-Free Machine Translation Evaluation
We systematically investigate a range of metrics based on state-of-the-art cross-lingual semantic representations obtained with pretrained M-BERT and LASER.
Behavior Cloning in OpenAI using Case Based Reasoning
Learning from Observation (LfO), also known as Behavioral Cloning, is an approach for building software agents by recording the behavior of an expert (human or artificial) and using the recorded data to generate the required behavior.
Learning High Order Feature Interactions with Fine Control Kernels
We provide a methodology for learning sparse statistical models that use as features all possible multiplicative interactions among an underlying atomic set of features.
WikiHist.html: English Wikipedia's Full Revision History in HTML Format
Wikipedia is written in the wikitext markup language.
Computers and Society
Quantifying Engagement with Citations on Wikipedia
Wikipedia, the free online encyclopedia that anyone can edit, is one of the most visited sites on the Web and a common source of information for many users.
Computers and Society
Robust Cross-lingual Embeddings from Parallel Sentences
Recent advances in cross-lingual word embeddings have primarily relied on mapping-based methods, which project pretrained word embeddings from different languages into a shared space through a linear transformation.
Cross-Lingual Document Classification
Document Classification
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Deep Learning for Prostate Pathology
For case usage, these models were applied for the annotation tasks in clinician-oriented pathology reports for prostatectomy specimens.
Auditing Radicalization Pathways on YouTube
Non-profits, as well as the media, have hypothesized the existence of a radicalization pipeline on YouTube, claiming that users systematically progress towards more extreme content on the platform.
Computers and Society Social and Information Networks
Privacy-Preserving Classification with Secret Vector Machines
Second, we implement SecVM's distributed framework for the Cliqz web browser and deploy it for predicting user gender in a large-scale online evaluation with thousands of clients, outperforming baselines by a large margin and thus showcasing that SecVM is suitable for production environments.
Privacy-Preserving Distributed Learning with Secret Gradient Descent
In many important application domains of machine learning, data is a privacy-sensitive resource.
Crosslingual Document Embedding as Reduced-Rank Ridge Regression
Finally, although not trained for embedding sentences and words, it also achieves competitive performance on crosslingual sentence and word retrieval tasks.
Eliciting New Wikipedia Users' Interests via Automatically Mined Questionnaires: For a Warm Welcome, Not a Cold Start
As such, these systems cannot make high-quality recommendations to newcomers without any previous interactions -- the so-called cold-start problem.
Hot Streaks on Social Media
We show that user impact tends to have certain characteristics: First, impact is clustered in time, such that the most impactful tweets of a user appear close to each other.
Social and Information Networks
Expanding the Text Classification Toolbox with Cross-Lingual Embeddings
In particular, we test the hypothesis that embeddings with context are more effective, by multi-tasking the learning of multilingual word embeddings and text classification; we explore neural architectures for CLTC; and we move from bi- to multi-lingual word embeddings.
Reverse-Engineering Satire, or "Paper on Computational Humor Accepted Despite Making Serious Advances"
Starting from the observation that satirical news headlines tend to resemble serious news headlines, we build and analyze a corpus of satirical headlines paired with nearly identical but serious headlines.
Measuring Societal Biases from Text Corpora with Smoothed First-Order Co-occurrence
The common approach to measuring such biases using a corpus is by calculating the similarities between the embedding vector of a word (like nurse) and the vectors of the representative words of the concepts of interest (such as genders).
Churn Intent Detection in Multilingual Chatbot Conversations and Social Media
To this end, we crowdsource and publish a dataset of churn intent expressions in chatbot interactions in German and English.
Quootstrap: Scalable Unsupervised Extraction of Quotation-Speaker Pairs from Large News Corpora via Bootstrapping
We propose Quootstrap, a method for extracting quotations, as well as the names of the speakers who uttered them, from large news corpora.
Growing Wikipedia Across Languages via Recommendation
The system involves identifying missing articles, ranking the missing articles according to their importance, and recommending important missing articles to editors based on their interests.
Social and Information Networks Digital Libraries
Exploiting Social Network Structure for Person-to-Person Sentiment Analysis
Person-to-person evaluations are prevalent in all kinds of discourse and important for establishing reputations, building social bonds, and shaping public opinion.
Compressive Feature Learning
This paper addresses the problem of unsupervised feature learning for text data.
