Polarity Classification of Arabic Sentiments

Al-Kabi, Mohammed N.; Wahsheh, Heider A.; Alsmadi, Izzat

doi:10.4018/ijitwe.2016070103

Cited by 12 publications

(3 citation statements)

References 29 publications

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“…It has been done through having the term frequency calculated. In pre-processing part, the removal of stop-word is done through using an algorithm based on the so-called "deterministic finite machine" [11].…”

Section: Related Workmentioning

confidence: 99%

“…In the meantime, other research works and literary studies have created lists of stop-words, still there has been no general and accepted stop-list or stop-word list for the texts of hadiths. For instance, AL-Kabi [11] recommended doing research work in the future on the impact of steps of pre-processing such as stemming and stop-word removal concerning the results of hadiths. Moreover, other researchers such as Alkhatib [12], Harrag [13], [14], [15], [16], Al-Kabi [17], Saeed and Jaffry [18], Hasan and Zakaria [19] have conducted researches on the Arabic texts of hadiths; however, they have not addressed to what extent a stop-list's use affects their research work.…”

Section: Related Workmentioning

confidence: 99%

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Generating Arabic Stop-Word for Hadith

Hazzaimeh¹,

Norwawi²,

Khalaf³

2019

MJoSHT

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Stop-words or (function words) play a great role in performing various functions in sentences, but are still typically inadequate to use for retrieval. They consist of several elements such as common nouns, pronouns and prepositions. With that, there are several Arabic particles available in the online Khoja and Abu EL-Khair stoplist taken from various websites. Arabic stop-words’ main problem lies in accepting the prefixes and suffixes’ attachment. In the current paper, a new methodology for generating a general stop-word list has been proposed and applied on hadiths. In detail, hadith is defined as words, acts, deeds, traditions, silent approvals and character of Prophet Muhammad S.A.W. (peace be upon him). The current paper aims at examining the effect of removing stopwords from verification of hadiths. The problem is that the previously generated stop-word lists have been on Modern Standard Arabic (MSA), which is the most commonly used language in hadiths. A stop-word list of Hadith and a corpus-based list has been created to be used in the process of hadith verification. The effectiveness and success of Hadith verification when using the newly generated lists along with earlier generated lists of MSA, combining the Hadith lists have been compared with the MSA lists. The Hadith verification has been performed using sequential pattern mining. Lastly, the experiments have demonstrated that the general lists comprising hadith words showed a better performance compared to using the lists of MSA stopwords.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Generating Arabic Stop-Word for Hadith

Hazzaimeh¹,

Norwawi²,

Khalaf³

2019

MJoSHT

View full text Add to dashboard Cite

show abstract

“…Beside the users textual opinions there are increasing number of audio and video contributing opinions on social networks, i.e. Twitter, Facebook and YouTube that could be converted into textual content as a way to be processed [2]. Figure 1 presents the growth of Facebook users in the Arab world during 2011-2017 [3] Opinion mining or sentiment analysis is the process of automatically analyzing, preprocessing, extracting the useful attributes (i.e.…”

Section: Introductionmentioning

confidence: 99%

Opinion Mining: How efficient are Online classification tools?

Khafajeh¹

2020

IJETER

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Recently, Online Social Networks (OSNs) are considered as important resource of information, since they provide a huge amount of data that reflects the interactions between users in various fields, such as: politics, sport and business. Opinion mining (or sentiment analysis) is a process that uses natural language processing, and text analysis methods to understand users' feelings or opinions, and detect their polarity, which could be positive, negative or neutral. The outcomes of opinion mining approaches help in extracting useful patterns that enable traders to take critical decisions for business, marketing and politics. In the literature, we have several proposed opinion mining systems, tools and approaches, but in general they are not available on public. Many other online opinion mining tools are simple to use and available for free or as demos. Opinion mining online tools performance need to be evaluated to attract researchers and companies utilizing their advantages. The main purpose of this study is to evaluate how efficient are online opinion mining tools for Arabic language. We used benchmark Arabic opinion collections and classify them using two popular online sentiment analysis tools that support Arabic language; Paralleldots and Repustate. The experiment used prediction quality measurement to evaluate these tools and compare their results with several machine learning classifiers in order to recommend the best available solution for Arabic sentiment analysis. Our results showed that Paralleldots API is highly recommended for Arabic sentiment analysis for both positive and negative reviews.

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QR Codes Cryptography: A Lightweight Paradigm

Wahsheh

Al-Zahrani²

2022

International Conference on Information Systems and Intelligent Applications

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Polarity Classification of Arabic Sentiments

Cited by 12 publications

References 29 publications

Generating Arabic Stop-Word for Hadith

Generating Arabic Stop-Word for Hadith

Opinion Mining: How efficient are Online classification tools?

QR Codes Cryptography: A Lightweight Paradigm

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