Unlabeled data is often used to learn representations which can be used to supplement baseline features in a supervised learner. For example, for text applications where the words lie in a very high dimensional space (the size of the vocabulary), one can learn a low rank “dictionary” by an eigendecomposition of the word co-occurrence matrix (e.g. using PCA or CCA). In this paper, we present a n...

In December 2019, a new pandemic called the coronavirus began ravaging world. By May 2020, had caused great loss of lives and disrupted way in more ways than one. The nature disease saw several strategies to curb its spread rolled out. These included closing businesses borders, restriction movements working from home, mask mandate among others. With these measures effects, many individuals have...

The rapid accumulation of data in social media (in million and billion scales) has imposed great challenges in information extraction, knowledge discovery, and data mining, and texts bearing sentiment and opinions are one of the major categories of user generated data in social media. Sentiment analysis is the main technology to quickly capture what people think from these text data, and is a r...

Currently, sentiment analysis into positive or negative getting more attention from the researchers. With rapid development of internet and social media have made people express their views opinion publicly. Analyzing in impact many fields such as services productions that companies offer. Movie reviewer needs processing to be prepared detect emotion, classify them achieve high accuracy. The di...

As websites, social networks, blogs, and online portals proliferate on the internet, authors are producing reviews, opinions, ideas, ratings, feedback. The emotional content of this writer may be about things like books, people, hotels, items, studies, events, so on. These emotions have great value for businesses, governments, people. majority writer-generated material requires usage text minin...

Information and news about Covid-19 received various responses from social media users, including Twitter users. Changes in netizen opinion time to are interesting analyze, especially the patterns of public sentiment emotions contained these opinions. Sentiment emotional conditions can illustrate public's response pandemic Indonesia. This research has two objectives, first reveal types that eme...

this article deals with two main issues: firstly, it investigates the status of sanai's poetry in the development of dehkhoda dictionary. to achieve this end, examples cited from sanai's poems by the authors of dehkhoda dictionary have been examined. the study reveals that in quite a good number of cases, sanai's poems have been the exclusive source for the borrowed examples and the dictionary ...

This paper presents a simple, robust and (almost) unsupervised dictionary-based method, qwn-ppv (Q-WordNet as Person-alized PageRanking Vector) to automatically generate polarity lexicons. We show that qwn-ppv outperforms other automatically generated lexicons for the four ex-trinsic evaluations presented here. It also shows very competitive and robust results with respect to manually annotated...

With the rise of social networking epoch, there has been a surge of user generated content. Microblogging sites have millions of people sharing their thoughts daily because of its characteristic short and simple manner of expression. We propose and investigate a paradigm to mine the sentiment from a popular real-time microblogging service, Twitter, where users post real time reactions to and op...

We present a lexicon-based approach to extracting sentiment from text. The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic orientation (polarity and strength), and incorporates intensification and negation. SO-CAL is applied to the polarity classification task, the process of assigning a positive or negative label to a text that captures the tex...