7 апр. 2014 г. ABSTRACT. Data about migration flows are largely inconsistent across coun- tries typically outdated
Twitter has brought much attention recently as a hot research topic in the domain of sentiment analysis. Training sentiment classifiers from tweets data often
Taken together these techniques enable the world's first automated endtoend spear phishing campaign generator for Twitter. This research and code are for
Sentiment detection of tweets is one of the basic analysis utility functions needed by various appli- cations over twitter data. Many systems and ap- proaches
4 авг. 2017 г. Twitter data was stored in the database and fur- ther processed (see Section 6) with language tools offered as Web services in a common ...
We use manually annotated Twitter data for our. 30. Page 2. experiments. One advantage of this data over pre- viously used data-sets
Twitter has built a Hadoop-based platform for large-scale data analytics running Pig [26 10] on a cluster of several hundred machines; see [19] for an earlier
24 окт. 2019 г. The second goal is to assist in the analysis of Twitter data via converting information returned by Twitter's APIs into tabular data structures ...
on degree of hateful intent and used it to annotate twitter data accordingly. The key contribution of this paper is the new dataset of tweets we created
Page 1. Your Twitter data. Your profile. Gender. Age.
How is Twitter data used in research?
Twitter data are widely used for research purposes and are collected through a variety of methods and tools. In this guide, we’ll show you easy methods for acquiring Twitter data, with some gestures toward specific types of spatial and social analyses.
Why is Twitter using MySQL?
Twitter has one of the biggest deployments of MySQL right from its inception. It has MySQL clusters with thousands of nodes serving millions of queries per second. 1. Acting as the storage node for the distributed data store within Twitter’s sharding framework.
What database does Twitter use to store metrics?
Metrics DB is used at Twitter to store the metrics. The metric ingestion rate is more than 5 billion metrics per minute with 25K query requests per minute. Originally, Manhattan was used as the metric storage database but Twitter faced scalability issues along with not having support for additional minute metric tags.