… aim to provide insight in the importance of semantics for multi-lingual sentiment analysis. …
In Section 2, we discuss related work on (multi-lingual) sentiment analysis and the semantic …

… Automated Sentiment Analysis techniques help save manpower, get faster output, sift through
massive unnecessary data to find relevant material, and present the results in necessary …

… Finally, it should be noted that the ultimate goal of CLSA is to help target languages
achieve sentiment analysis with the help of source languages. Due to the large amounts of …

… learning by conducting some early empirical analyses. … three languages for emotion
recognition using support vector … is the accuracy in the sentiments analysis. We used benchmark …

… While a manually annotated lexicon or corpus is still vital for sentiment analysis, it requires
financial funding support and a considerable amount of human effort to create a reasonably …

… We then go on to find complex collocation patterns that help in unambiguously detecting
the sentiment words – this is revealed to us during the evaluation phase after processing …

… But some of the tweets are posted in the undefined language, this type of tweets will not
support for the language translations and sentiment analysis. So it is better to avoid undefined …

… sentiment of the text based on these sentence representations. Besides models evaluation
on PolEmo 1.0 Sentiment … the sentiment of the texts in MultiEmo-Test 1.0 Sentiment Corpus, …

… These features help in training of the Naïve Bayes classifier model. … Some of the more
difficult challenges of Sentimental Analysis could also be used for further extensions of this study. …

… -languages text sentiment … text source composed by reviews all written in different languages,
without any code-switching indication, or language translation. We construct a multi-lingual …