Sentiment Analysis With 3RDi Search: Facts You Should Know
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Sentiment analysis is the technology that determines the exact sentiment behind a text or content. Also referred to as opinion mining, sentiment analysis is based on artificial intelligence (AI) and makes use of NLP, linguistics, and advanced text analysis to come to the right conclusion about the sentiment behind the said piece of content. This is an amazing concept because it identifies the thought hidden behind the words without the need for human intervention. There are multiple uses of sentiment analysis and it is a concept that is revolutionizing the field of customer service and client interactions for enterprises.
Sentiment analysis is an integral part of text analysis and it is used by enterprises to get the insights required for identifying customer sentiments for a particular brand or product. This technology is also frequently used to understand the trends on social media. The new age enterprise search platform of today offers sentiment analysis as one of its many text analysis functionalities.
3RDi Search is an enterprise search platform that is a comprehensive suite of text analysis capabilities. Sentiment analysis is one of the features of 3RDi Search. However, in order to understand how 3RDi Search can help enterprises figure out the sentiment behind plain text or social media feed, we must make ourselves familiar with some key facts about sentiment analysis.
Key Facts about Sentiment Analysis
Here are some facts about sentiment analysis that one should know. So, let's have a look at them.
There are four types of sentiment analysis
Sentiment analysis is more commonly classified into the following four types:
a] Fine-Grained Sentiment Analysis
This type is used to interpret product ratings and reviews and requires you to define polarity categories, starting from 'Very positive' to 'Very negative'.
b] Detection of Emotion
The second type of sentiment analysis is about identifying the emotions in a text or any piece of content. It is about analyzing whether the writer or speaker is happy, angry, sad or frustrated, with the help of complex algorithms.
c] Aspect-Based Sentiment Analysis
This type of sentiment analysis is about identifying the aspect of the product or brand that is being talked about. For example, if it's a review of a pair of shoes, the objective would be to find out if people are talking about the colour, style, comfort or any other aspect in particular.
d] Multilingual Sentiment Analysis
The most complex of all types, multilingual sentiment analysis is possible only with the use of advanced algorithms. In addition to the use of sentiment lexicons, one needs to create specific programming to enable the machine to identify particular languages.
Significance of Sentiment Analysis
One might wonder why sentiment analysis is such a buzzword right now. The reason is simple – enterprise data is not anything like the data we see on the Web. It is unoptimized and unstructured and cannot be analyzed manually or through the conventional keyword-based approach.
So, how do you identify the context of the information hidden within this data? You need advanced AI-driven technology for this and that's exactly what sentiment analysis does. It helps enterprise search tools like 3RDi Search derive the emotions used and context behind unstructured data.
Key Benefits of Sentiment Analysis
The following are the key benefits:
So, that was about the significant things to know about sentiment analysis using the new-age enterprise search platform like 3RDi Search. Want to explore the text analysis capabilities of 3RDi Search? Visit www.3rdisearch.com or drop us an email at
Sentiment analysis is an integral part of text analysis and it is used by enterprises to get the insights required for identifying customer sentiments for a particular brand or product. This technology is also frequently used to understand the trends on social media. The new age enterprise search platform of today offers sentiment analysis as one of its many text analysis functionalities.
3RDi Search is an enterprise search platform that is a comprehensive suite of text analysis capabilities. Sentiment analysis is one of the features of 3RDi Search. However, in order to understand how 3RDi Search can help enterprises figure out the sentiment behind plain text or social media feed, we must make ourselves familiar with some key facts about sentiment analysis.
Key Facts about Sentiment Analysis
Here are some facts about sentiment analysis that one should know. So, let's have a look at them.
There are four types of sentiment analysis
Sentiment analysis is more commonly classified into the following four types:
a] Fine-Grained Sentiment Analysis
This type is used to interpret product ratings and reviews and requires you to define polarity categories, starting from 'Very positive' to 'Very negative'.
b] Detection of Emotion
The second type of sentiment analysis is about identifying the emotions in a text or any piece of content. It is about analyzing whether the writer or speaker is happy, angry, sad or frustrated, with the help of complex algorithms.
c] Aspect-Based Sentiment Analysis
This type of sentiment analysis is about identifying the aspect of the product or brand that is being talked about. For example, if it's a review of a pair of shoes, the objective would be to find out if people are talking about the colour, style, comfort or any other aspect in particular.
d] Multilingual Sentiment Analysis
The most complex of all types, multilingual sentiment analysis is possible only with the use of advanced algorithms. In addition to the use of sentiment lexicons, one needs to create specific programming to enable the machine to identify particular languages.
Significance of Sentiment Analysis
One might wonder why sentiment analysis is such a buzzword right now. The reason is simple – enterprise data is not anything like the data we see on the Web. It is unoptimized and unstructured and cannot be analyzed manually or through the conventional keyword-based approach.
So, how do you identify the context of the information hidden within this data? You need advanced AI-driven technology for this and that's exactly what sentiment analysis does. It helps enterprise search tools like 3RDi Search derive the emotions used and context behind unstructured data.
Key Benefits of Sentiment Analysis
The following are the key benefits:
- Saves time and efforts required to analyze large volumes of data manually
- Helps businesses accurately process large volumes of data in a cost-effective manner
- Analysis of complex data in real time helps in identifying areas of improvement without wasting any time
- Offers higher levels of accuracy when analyzing the sentiment behind enterprise data
So, that was about the significant things to know about sentiment analysis using the new-age enterprise search platform like 3RDi Search. Want to explore the text analysis capabilities of 3RDi Search? Visit www.3rdisearch.com or drop us an email at
Explore more about Enterprise Search with 3RDi Search. Read Exploring the 3RDi Search Advantage for Enterprise Search.
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