# Analyzing the Effect of Negation in Sentiment Polarity of Facebook Dialectal Arabic Text
## 2 Background
### Valence Shifters  
Sentiment analysis is predicated upon the concept that words, words sequence, and words group can determine a sentiment value. Hence, some lexical items communicate either negative or positive valence or attitude [13]. For example, the verb \"boost\" gives a positive valence, whereas \"discourage\" gives a negative valence. Some words have a positive valence, and, however, when a valence shifter, such as negation, enters the sentence, it becomes negative. For example, \"[PERSON] is clever\" versus \"[PERSON] is not clever\". When a word with a positive valence is combined with a negation such as not, the valence changed from positive to negative. The author in [13] describes significant determiners of sentiment in terms of valence shifters, which are words that modify the polarity of a sentiment of another word. For example, valence shifters can intensify a sentiment such as \"so\" in \"so strong\". Valence shifters can also weaken a sentiment such as \"slightly\" in \"slightly hard\". Valence shifters can even invert sentiment such as \"not\" in \"not easy\". The English language has Valence shifters divided into two main categories that are either based on sentence or discourse. Valence shifters that are Sentence-based can be categorized in terms of inverters, intensifiers, modals, pre-suppositional items, and irony:  
* Inverters: These are words that change the polarity of a word from positive to negative and vice versa, for example, \"not\", \"never\", \"none\", \"neither \". Saying \"not bad at all\" changes the polarity from negative to positive; however, saying \"not good\" changes the polarity from positive to negative. * Intensifiers can amplify the sentiment, for example: \"badly\" in \"badly injured\"; others make the meaning of the word weak, such as \"slightly\" in \"slightly interested\". Their impact is not consistent in the language context; their position can significantly influence their effect. * Modals: words which may be used to assume future consequences, hence they convey a probability of an even happening. Words related to opinions may not give normal behavior, such as \"If [PERSON] were lazy, he would fail in their exams\". The words \"lazy\" and \"fail\" are negative; however, \"would\" and \"was\" affected the sentiment of the negative words. Thus, the sentence sentiment is that [PERSON] is not lazy not likely to fail in the exam. * Pre-suppositional Items: these words can affect the valence when an event does not meet the confident expectation. For example, the word \"almost\" in \"he almost passed\" implies that the person did not pass. The word \"passed\" conveys a positive sentiment but \"almost\" changed the sentiment to a negative one. This also applies to \"barely\" in \"the water was barely enough\". In both examples, the pre-suppositional items negatively shifted the neutral and positive sentiment. Some parts of speech may affect the sentiment in a similar way, such as saying \"failed to pass\" or \"impossible to enjoy\". * Irony is the last category of sentence valence shifters we consider here. Context plays a significant role in its recognition and impact, to the extent that readers may not consistently identify an invention of sentiment. The irony arises when some words are used to intensify the sentiment but flip the polarity. The word \"genius\" is a positive word that can give a negative sentiment such as \"the genius student did not solve the exercise\". Discourse-based valence shifters are concerned with sentence structure. In general, they show that the valence of a sentence cannot be assumed to be a simple composition of the valence of the clauses involved. Hence, in the case of DA, where grammar rules are not followed, their relevance to our analysis context is limited. Discourse-based valence shifters include the following:  
* Particular conjunctions that combine clauses such as \"but\", \"although\", and \"however\" can affect words that show opinions within their range.