Arabic Social Media Listening & Sentiment Analysis
To best understand their customers, companies must analyze the original languages they express themselves in through social posts, online reviews, and customer surveys. There are few areas of the globe where this is more true than in the Arabic speaking world, especially in the Middle East and North Africa. There are over 300-million Arab speaking people globally. Yet, understanding formal Arabic is challenging enough, once you layer on that there are over 30 Arabic dialects, intermingled with English and sprinkled with street language, then you begin to understand one of social media listening’s greatest linguistic challenges. Understanding Arabic consumers requires a unique approach and a special set of text mining and sentiment analysis tools.
The Challenge: Arabic Dialects, Social Media and Sentiment Analysis
Social media listening and sentiment analysis allow brands the opportunity to know what consumers are saying about their products and experiences, and how they feel about them. Are mentions positive, negative or just meh? Are they mostly about price, product, quality or customer service? These types of insights can help brands improve their offerings, increase sales and drive market share.
Sounds easy? It’s not. Social media is the internet’s playground and laboratory for the use, misuse, and creative shaping of everyday language. It’s a place where people go to communicate, not to properly conjugate verbs. Social media is both blessed and damned by linguistic nuance. Its abundance of slang, acronyms, idioms, homonyms, misspellings, sarcasm, emojis, emoticons, and neologisms often make it hard for not only humans but machines as well, to comprehend what is being said in social posts. What is an even bigger challenge to social media listening companies is interpreting social posts written in languages other than English, and then in one regional dialect of another for those languages.
Not all languages are the same; grammar rules vary from one language to another and the rules of verb conjugation, noun-verb agreement, and negations vary from one language to another. This can make it extremely difficult to perform text analytics without the proper tools in place to understand the nuances of other languages.
What are Arabic Dialects?
There over 30 Arabic dialects derived from what is called Modern Standard Arabic. Modern Standard Arabic, or MSA for short, is the standard version of Arabic, often referred to as Classical Arabic, or the Arabic of the Quran. It is taught in schools and is usually used in formal writing and speech. Literature and poetry, especially earlier forms, are written in MSA. It is often found in business, books, newspapers, and other mass media, but not necessarily social media where dialects appear more frequently. Considered the official language of more than 20 countries, it is spoken by over 300-million people globally. Dialects are variations of MSA usually rooted in geo-regional dialogue patterns in conversational language. These vernacular or colloquial dialects often possess different grammars, vocabularies, semantics, and syntax.
Which are the most used Arabic dialects?
Many can be understood by speakers of other Arabic dialects, while some differ so significantly that they are barely recognizable. Here are just a few of the largest Arabic language variations used by around 35% of the Arabic speakers:
Gulf or Peninsular Arabic
Gulf or Peninsular Arabic refers to the several varieties of Arabic spoken by people in the Arabian Peninsula. This type of Arabic is used by over 7-million people for everyday conversations and social media in countries such as Saudi Arabia, Yemen, and the United Arab Emirates. One can also find it being used on Twitter and other social media in Bahrain, Qatar, and Kuwait.
Egyptian Arabic is the most widely spoken and studied Arabic dialect with a total of 68-million speakers in Egypt. It is also spoken in those countries where Egyptians have migrated especially throughout North Africa and the Middle East. Although the dialect shares the same vocabulary as Modern Standard Arabic, it’s grammar and sentence structure are different.
Levantine Arabic has two different varieties and is used in the Eastern part of the Middle East. North Levantine Arabic is spoken in countries such as Syria and Lebanon. On the other hand, the South Levantine variety is used across Israel, Jordan, and Palestine. This vernacular language is used by 30-million people worldwide.
These dialects, as well as 20 others, are used by Arab speakers across social media to varying degrees, often mixed with MSA, English, and other languages such as French in the case of Morocco or Tunisia. Social media listening and sentiment analysis look to understand these dialects using a combination of artificial intelligence, machine learning, and expertise in natural language processing (NLP). This provides brands the opportunity to extract insights from Arabic, a language dense with dialects and complexity.
Social Media Use in the Middle East: 10 Stats You Should Know!
One of the greatest errors made by marketers and researchers looking for brand insights is the belief that Arabic speakers do not use social media. The reality is that they are heavy users of social media. Here are 10 important statistics from 2019 on social media use in the Middle East and North Africa that quickly dispel that myth:
- Mobile social media penetration in the region has more than doubled to 44% in the past five years,
- 9 out of 10 young Arabs use at least one social media channel every day,
- Facebook now has 187 million active monthly users in the region.
- Egypt is the largest market for Facebook in MENA. It is home to 38 million daily users and 40 million monthly users.
- Saudi Arabia and Turkey are the fifth and sixth largest markets for Twitter in the world. More than 10 million users are active on the social network in Saudi Arabia.
- Up to 72% of Twitter users in KSA and UAE, and 62% of users in Egypt, consider Twitter one of their main sources for online video content.
- There are more than 63 million users of Instagram in the Middle East.
- Saudi Arabia is the fifth largest market for Snapchat in the world, with over 15.65 million users.
- WhatsApp is the most used Facebook-owned service, with 75% penetration.
- More than 60% of YouTube viewers in MENA are millennials. In Egypt, 77% of millennials watch YouTube every day.
Thus far we have shown the challenges posed to Arabic sentiment analysis by various dialects of the language. In addition, it is clearer now that the Middle East and North Africa provide a treasure of consumer and brand insights as expressed through social media. Next, we will look into how Repustate’s Arabic Text Analytics API provides companies and brands to fully leverage Arabic text data at their disposal if they look to grow market share in the area.
Should translations be used for Arabic sentiment analysis?
Arabic is a unique language and it differs from English in a number of ways: from sentence structure to words and phrases that may be used differently, using the same techniques and language models that work for English sentiment analysis when conducting Arabic sentiment analysis would yield terribly inaccurate results.
Arabic Sentiment Analysis API
Because of the challenges for applying high-level sentiment analysis for Arabic companies, Repustate has developed Arabic-specific tools to decipher words, industry jargon, and the feelings behind your customer’s words. Arabic sentiment analysis API includes an Arabic part of speech tagger, an Arabic lemmatizer, and of course, Arabic-specific sentiment models. The tool is also capable of identifying, extracting and applying sentiment analysis to dialects such as Egyptian, Levantine and Gulf.
What are the basic steps in Arabic sentiment analysis?
Arabic part-of-speech tagging allows us to narrow in on where the sentiments may lie within a block of text. Verbs, nouns, and adjectives provide the cues necessary to determine sentiment and aid in detailed analysis. In order to create a fast and accurate Arabic part-of-speech tagger, data scientists have to have a massive corpus of manually tagged Arabic text. This text can then be fed into a machine-learning algorithm to create an Arabic part-of-speech tagger.
The larger the corpus, and more importantly, the more varied the corpus, the better the results in creating the Arabic part-of-speech tagger. Repustate has created a massive corpus of Arabic text grabbing data from a variety of sources to ensure good coverage. Taking it a step further, by using Arabic Named Entity Recognition with the advanced semantic search for enterprises, we can identify brand and business entities in data. No matter how misspelled a word is, our API will reproduce the first name in native script and thus improve the accuracy of name searching, transliteration, and the grade of identity verification initiatives. This gives high accuracy ranked results, on the basis of the linguistic, phonetic, and specific cultural variation patterns of the names
Arabic language sentiment models
Repustate has developed sentiment language models specific to Arabic to capture the various phrases, idioms, and expressions that help define sentiment when writing in Arabic. Understanding the various grammatical aspects of the Arabic language that make it unique and very different from English is what allows Repustate’s Arabic sentiment analysis to be as fast and as accurate as it is.
Applications of Sentiment Analysis Tools:
Analyze Twitter, Facebook, Instagram, and Youtube content:People love to express their experiences online in the form of product reviews, recommendations, and even tutorials. So be it through Facebook, Twitter, YouTube, or Instagram, now you can analyze sentiment in this massive flow of information to understand how your customers perceive you and your competitors. Unlock the power of Arabic social media with Repustate’s social media listening solution.
What are the benefits of Repustate’s Arabic Sentiment Analytics Tool?
Here are the benefits of using our sentiment analyses tool:
- Understand your Arabic-speaking customers accurately and quickly.
- Identify and analyze the 3 largest and most popular Arabic dialects.
- Access to a Visual Command Centre for near-time analysis.
- Granular Arabic sentiment analysis by aspect.
- Flexible deployment On-Premise or through Cloud.
- Custom model that can be catered to your brand, domain and dialect.
- Multilingual Sentiment Analysis available to scale globally fast.
Give your Arabic Customers a Voice
Get fast, reliable, and accurate results every time, no matter what language your customers speak, be it Arabic, Turkish, French or English. Our multilingual sentiment analysis solution understands and can effectively process information in over 23 different languages.