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Understandable big data: a survey
This survey presents the concept of Big Data. Firstly, a definition and the features of Big Data
are given. Secondly, the different steps for Big Data data processing and the main problems …
are given. Secondly, the different steps for Big Data data processing and the main problems …
Location reference recognition from texts: A survey and comparison
A vast amount of location information exists in unstructured texts, such as social media
posts, news stories, scientific articles, web pages, travel blogs, and historical archives …
posts, news stories, scientific articles, web pages, travel blogs, and historical archives …
A replicable comparison study of NER software: StanfordNLP, NLTK, OpenNLP, SpaCy, Gate
Named Entity Recognition (NER) is a key building block of any Natural Language
Processing (NLP) system, making possible the detection and classification of entities (eg …
Processing (NLP) system, making possible the detection and classification of entities (eg …
Exploiting context for rumour detection in social media
Tools that are able to detect unverified information posted on social media during a news
event can help to avoid the spread of rumours that turn out to be false. In this paper we …
event can help to avoid the spread of rumours that turn out to be false. In this paper we …
Who cares about sarcastic tweets? investigating the impact of sarcasm on sentiment analysis
Sarcasm is a common phenomenon in social media, and is inherently difficult to analyse, not
just automatically but often for humans too. It has an important effect on sentiment, but is …
just automatically but often for humans too. It has an important effect on sentiment, but is …
Twitter as a lifeline: Human-annotated twitter corpora for NLP of crisis-related messages
Microblogging platforms such as Twitter provide active communication channels during
mass convergence and emergency events such as earthquakes, typhoons. During the …
mass convergence and emergency events such as earthquakes, typhoons. During the …
Learning reporting dynamics during breaking news for rumour detection in social media
Breaking news leads to situations of fast-paced reporting in social media, producing all
kinds of updates related to news stories, albeit with the caveat that some of those early …
kinds of updates related to news stories, albeit with the caveat that some of those early …
[PDF][PDF] Twitter part-of-speech tagging for all: Overcoming sparse and noisy data
Part-of-speech information is a pre-requisite in many NLP algorithms. However, Twitter text
is difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style. We …
is difficult to part-of-speech tag: it is noisy, with linguistic errors and idiosyncratic style. We …
Location extraction from social media: Geoparsing, location disambiguation, and geotagging
Location extraction, also called “toponym extraction,” is a field covering geoparsing,
extracting spatial representations from location mentions in text, and geotagging, assigning …
extracting spatial representations from location mentions in text, and geotagging, assigning …
Discourse-aware rumour stance classification in social media using sequential classifiers
Rumour stance classification, defined as classifying the stance of specific social media posts
into one of supporting, denying, querying or commenting on an earlier post, is becoming of …
into one of supporting, denying, querying or commenting on an earlier post, is becoming of …