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In this paper, we focus on a recent Web trend called microblogging, and in particular a site called Twitter. The content of such a site is an extraordinarily large number …...

In this paper, we describe our system which participated in the SemEval 2010 task of disambiguating sentiment ambigu- ous adjectives for Chinese. Our system uses text messages from Twitter, a …...

Twitter is an online social networking, which has become an important source of information for marketing strategies and online reputation management. In this paper, we probe the problem of organization …...

While there have been many studies on measuring the size of learners’ vocabulary or the vocabulary they should learn, there have been few studies on what kind of words learners …...

We present a novel topic modelling-based methodology to track emerging events in microblogs such as Twitter. Our topic model has an in-built update mechanism based on time slices and implements …...

Text prediction is the task of suggesting text while the user is typing. Its main aim is to reduce the number of keystrokes that are needed to type a text. …...

With the rapid growth of social media, Twitter has become one of the most widely adopted platforms for people to post short and instant message. On the one hand, people …...

Social Media contain a multitude of user opinions which can be used to predict real- world phenomena in many domains in- cluding politics, finance and health. Most existing methods treat …...

Work on authorship attribution has tradition- ally focused on long texts. In this work, we tackle the question of whether the author of a very short text can be successfully …...

The widespread use of Twitter makes it very interesting to determine the opinions and the sentiments expressed by its users. The short- ness of the length and the highly informal …...

Hidden properties of social media users, such as their ethnicity, gender, and location, are of- ten reflected in their observed attributes, such as their first and last names. Furthermore, users …...

Twitter has been shown to be a fast and reli- able method for disease surveillance of com- mon illnesses like influenza. However, previ- ous work has relied on simple content …...

Most of the recent literature on Sentiment Analysis over Twitter is tied to the idea that the senti- ment is a function of an incoming tweet. However, tweets are filtered …...

The intersection of psychology and computational linguistics is capable of providing novel au- tomated insight into the language of everyday cognition through analysis of micro-blogs. While Twitter is often seen …...

We propose a Bayesian method of esti- mating a conditional distribution of data given metadata (e.g., the usage of a di- alectal variant given a location) based on queries from …...

AbstractSentiment classification over Twitter is usually affected by the noisy nature (abbreviations, irregular forms) of tweets data. A popular procedure to reduce the noise of textual data is to remove …...

This paper presents a machine learning approach to sarcasm detection on Twitter in two lan- guages – English and Czech. Although there has been some research in sarcasm detection in …...

Previous studies have shown that health reports in social media, such as Dai- lyStrength and Twitter, have potential for monitoring health conditions (e.g. adverse drug reactions, infectious diseases) in par- …...

Twitter is often used in quantitative stud- ies that identify geographically-preferred topics, writing styles, and entities. These studies rely on either GPS coordinates at- tached to individual messages, or on …...

A simile is a comparison between two essentially unlike things, such as “Jane swims like a dolphin”. Similes often ex- press a positive or negative sentiment to- ward something, but …...

Named entity recognition (NER) systems trained on newswire perform very badly when tested on Twitter. Signals that were reliable in copy-edited text disappear almost entirely in Twitter’s informal chatter, requiring …...

AbstractDuring the 2016 United States presidential election, politicians have increasingly used Twitter to express their beliefs, stances on current political issues, and reactions concerning national and international events. Given the …...

AbstractSentiment Analysis systems aims at detecting opinions and sentiments that are expressed in texts. Many approaches in literature are based on resources that model the prior polarity of words or …...

AbstractSocial media outlets are providing new opportunities for harvesting valuable resources. We present a novel approach for mining data from Twitter for the purpose of building transliteration resources and systems. …...

Sentiment Analysis (SA) is an active research area nowadays due to the tremendous interest in aggregating and evaluating opinions being disseminated by users on the Web. SA of English has …...

AbstractBecause of the increasing popularity of social media, much information has been shared on the internet, enabling social media users to understand various real world events. Particularly, social media-based infectious …...

Automated geolocation of social media mes- sages can benefit a variety of downstream ap- plications. However, these geolocation sys- tems are typically evaluated without attention to how changes in time …...

Social media sites such as Twitter are attractive sources of information due to their combination of accessibility, timeli- ness and large data volumes. Identifica- tion of medical entities in Twitter …...

Automatically recognising medical con- cepts mentioned in social media messages (e.g. tweets) enables several applications for enhancing health quality of people in a community, e.g. real-time monitoring of infectious diseases …...

AbstractMultiword Expressions (MWEs) are crucial lexico-semantic units in any language. However, most work on MWEs has been focused on standard monolingual corpora. In this work, we examine MWE usage on …...

AbstractWe describe a strategy for the acquisition of training data necessary to build a social-media-driven early detection system for individuals at risk for (preventable) type 2 diabetes mellitus (T2DM). The …...

AbstractEmojis allow us to describe objects, situations and even feelings with small images, providing a visual and quick way to communicate. In this paper, we analyse emojis used in Twitter …...

AbstractSocial media collect and spread on the Web personal opinions, facts, fake news and all kind of information users may be interested in. Applying argument mining methods to such heterogeneous …...

AbstractFraming is a political strategy in which politicians carefully word their statements in order to control public perception of issues. Previous works exploring political framing typically analyze frame usage in …...

This paper presents a multi-domain interests dataset to train and test Recommender Systems, and the methodology to create the dataset from Twitter messages in English and Italian. The English dataset …...

AbstractWritten communication lacks the multimodal features such as posture, gesture and gaze that make it easy to model affective states. Especially in social media such as Twitter, due to the …...

This paper introduces the three SSIX corpora for sentiment analysis. These corpora address the need to provide annotated data for supervised learning methods. They focus on stock-market related messages extracted …...

AbstractIn this paper, we leverage social media platforms such as twitter for developing corpus across multiple languages. The corpus creation methodology is applicable for resource-scarce languages provided the speakers of …...

AbstractIn this paper we describe the system used by the ValenTO team in the shared task on Irony Detection in English Tweets at SemEval 2018. The system takes as starting …...

AbstractEvery day, the emotion and opinion of different people across the world are reflected in the form of short messages using microblogging platforms. Despite the existence of enormous potential introduced …...

AbstractThis paper describes our system submitted to SemEval 2019 Task 7: RumourEval 2019: Determining Rumour Veracity and Support for Rumours, Subtask A (Gorrell et al., 2019). The challenge focused on …...

AbstractThe massive amount of multi-formatted information available on the Web necessitates the design of software systems that leverage this information to obtain knowledge that is valid and useful. The main …...

AbstractTwitter is used for various applications such as disaster monitoring and news material gathering. In these applications, each Tweet is classified into pre-defined classes. These classes have a semantic relationship …...

AbstractOptimal language acquisition via reading requires the learners to read slightly above their current language skill level. Identifying material at the right level is the essential role of automatic readability …...

AbstractStance detection in twitter aims at mining user stances expressed in a tweet towards a single or multiple target entities. To tackle this problem, most of the prior studies have …...

AbstractContextualized word embeddings such as ELMo and BERT provide a foundation for strong performance across a wide range of natural language processing tasks by pretraining on large corpora of unlabeled …...

AbstractNowadays, social media credibility is a pressing issue for each of us who are living in an altered online landscape. The speed of news diffusion is striking. Given the popularity …...

AbstractThe widespread usage of Twitter during emergencies has provided a new opportunity and timely resource to crisis responders for various disaster management tasks. Geolocation information of pertinent tweets is crucial …...

AbstractIdentifying irony in user-generated social media content has a wide range of applications; however to date Arabic content has received limited attention. To bridge this gap, this study builds a …...

AbstractReading comprehension (RC) on social media such as Twitter is a critical and challenging task due to its noisy, informal, but informative nature. Most existing RC models are developed on …...

AbstractWe propose UPSA, a novel approach that accomplishes Unsupervised Paraphrasing by Simulated Annealing. We model paraphrase generation as an optimization problem and propose a sophisticated objective function, involving semantic similarity, …...

AbstractOffensive language detection is one of the most challenging problem in the natural language processing field, being imposed by the rising presence of this phenomenon in online social media. This …...

AbstractPredicting the political bias and the factuality of reporting of entire news outlets are critical elements of media profiling, which is an understudied but an increasingly important research direction. The …...

AbstractStance detection on social media can help to identify and understand slanted news or commentary in everyday life. In this work, we propose a new model for zero-shot stance detection …...

The widespread use of social networking ser- vices (SNSs) such as Twitter and Facebook in recent years have rendered it easy to in- teract with various people all over the …...

AbstractSifting French Tweets to Investigate the Impact of Covid-19 in Triggering Intense Anxiety. Social media can be leveraged to understand public sentiment and feelings in real-time, and target public health …...

AbstractThe language of Twitter differs significantly from that of other domains commonly included in large language model training. While tweets are typically multilingual and contain informal language, including emoji and …...

AbstractAutomatic depression detection on Twitter can help individuals privately and conveniently understand their mental health status in the early stages before seeing mental health professionals. Most existing black-box-like deep learning …...

AbstractDuring natural disasters, people often use social media platforms, such as Twitter, to post information about casualties and damage produced by disasters. This information can help relief authorities gain situational …...

AbstractHuman-annotated data plays a critical role in the fairness of AI systems, including those that deal with life-altering decisions or moderating human-created web/social media content. Conventionally, annotator disagreements are resolved …...