Add to ORKGShort texts, due to their nature which makes them full of abbreviations and new coined acronyms, are not easy to classify. Text enrichment is emerging in the literature as a potentially useful tool. This paper is a part of a longer term research that aims at understanding the effectiveness of tweet enrichment by means of news, instead of the whole web as a knowledge source. Since the choice of a news collection may contribute to produce very different outcomes in the enrichment process, we compare the impact of three features of such collections: volume, variety, and freshness. We show that all three features have a significant impact on categorization accuracy. Copyright \ua9 2016 for the individual papers by the paper's authors
Social media are a powerful communication tool in our era of digital information. The large amount o...
The growing number of twitter users create large amounts of messages that contain valuable informati...
Processing of raw text is the crucial first step in text classification and sentiment analysis. Howe...
We address the problem of the categorization of short texts, like those posted by users on social ne...
The widespread diffusion of mobile devices, e.g., smartphones and tablets, has made possible a huge ...
While it is widely recognized that streams of social media messages contain valuable information, su...
Two challenging issues are notable in tweet clustering. Firstly, the sparse data problem is serious ...
With each passing minute, online data is growing exponentially. A bulk of such data is generated fro...
The rise of social networks powered by the emergence of Web 2.0 unleashed a massive amount of gene...
Twitter is a worldwide social media platform where millions of people frequently express ideas and o...
Researchers on social-media understandably assert that the contributions social media has made on va...
The goal of this paper is to evaluate specific event-related Twitter posts, called tweets, for their...
Twitter represents a massively distributed information source over a kaleidoscope of topics ranging ...
In this thesis, we seek to find suitable methods for detecting news on Twitter within the fields of ...
Twitter has drew a large number of users to share and disperse most onward data, bringing about larg...
Social media are a powerful communication tool in our era of digital information. The large amount o...
The growing number of twitter users create large amounts of messages that contain valuable informati...
Processing of raw text is the crucial first step in text classification and sentiment analysis. Howe...
We address the problem of the categorization of short texts, like those posted by users on social ne...
The widespread diffusion of mobile devices, e.g., smartphones and tablets, has made possible a huge ...
While it is widely recognized that streams of social media messages contain valuable information, su...
Two challenging issues are notable in tweet clustering. Firstly, the sparse data problem is serious ...
With each passing minute, online data is growing exponentially. A bulk of such data is generated fro...
The rise of social networks powered by the emergence of Web 2.0 unleashed a massive amount of gene...
Twitter is a worldwide social media platform where millions of people frequently express ideas and o...
Researchers on social-media understandably assert that the contributions social media has made on va...
The goal of this paper is to evaluate specific event-related Twitter posts, called tweets, for their...
Twitter represents a massively distributed information source over a kaleidoscope of topics ranging ...
In this thesis, we seek to find suitable methods for detecting news on Twitter within the fields of ...
Twitter has drew a large number of users to share and disperse most onward data, bringing about larg...
Social media are a powerful communication tool in our era of digital information. The large amount o...
The growing number of twitter users create large amounts of messages that contain valuable informati...
Processing of raw text is the crucial first step in text classification and sentiment analysis. Howe...