With the evolution of technology and the growth of social media platforms, the interactions between businesses and customers are rapidly evolving. This has led to the generation of vast volumes of unstructured data. Every industry, company or organisation collects such data and requires that it is transformed into valuable, actionable insights that can be applied for business growth.
If the raw data retrieved from digital platforms are not analysed and transformed into structured data, further analysis is not possible. Industries require meaningful insights that can help them make data-driven decisions, create operational efficiencies, and value improvement.
Sentiment Analysis (SA) can…
The modern world has given rise to many options, which has made the customers more knowledgeable and picky. While Newton’s third law can be added in practical scenarios, social media has given it a new angle — “Every action has an equal and opposite reaction and social media overreaction.” Companies now can not ignore the potential that customer experience holds.
Customers can give their opinion about a product or service in multiple ways; by tweeting it, commenting on the company’s page, writing an email, taking up a survey, etc. The data, although accessible, is huge in numbers to sort through…
Data Analytics has been progressively considered as an enabling factor to leverage health data for a competitive edge. By using various machine learning techniques and text analytics tools, insights can play a constructive role in different medical and operational aspects including diagnosis, health monitoring & evaluation, healthcare planning, and management of hospitals.
One of the major challenges for healthcare analytics is to study huge data volumes that come in the form of unstructured text. Examples include nursing notes, clinical agreements, medical prescriptions, medical publications, and many more. …
Text Analytics is a machine learning technique that can interpret huge amounts of unstructured data which presents itself in the form of survey responses, feedback, chats, reviews, comments, emails, documents, records, data, and much more. Text Analytics or text mining can discover insights, trends, and structure. Tools like Sentiment Analysis, Emotion Detection, Topic Modeling, Named Entity Recognition, Offensive Language Detection, Tagging, Intent Analysis can help companies to understand the story behind the numbers and make informed decisions.
Industries That Can Benefit:
In the hospitality industry, reviews and feedback play a critical role in uplifting the company. One can…
Emotions play a huge part in human experience, and several times, they affect our decision-making abilities. How?
Have you ever noticed that we tend to repeat the activities that make us happy and avoid those that make us sad?
In the digital world, information spreads very quickly, and most of our interactions are filled with words that express our feelings and emotions. If these emotions are undealt with, more than often, they tend to intensify and spread like wildfire.
Natural Language Processing (NLP) has enabled us to detect such emotions from written text such as reviews, publications, recommendations, conversations, etc…
We can describe Offensive Language Detection as identifying abusive behaviours, such as hate speech, offensive language, sexism, and racism, in any text-related conversation on digital platforms.
We can also refer to it as Hate Speech Detection, Abuse Detection, Flame, or Cyberbullying Detection.
In recent years, with the increased use of social media platforms, human interactions are becoming rapid and informal at the same time. Administrators of these platforms are using extensive methods to check inappropriate behaviour and language.
In almost any social community, we can find offensive language in text formats such as text messages, instant messages, social media messages…
Misplaced IT Focus. Extremely High Costs. Poor Security. Outdated Technology. Poor Communication. Do any of these problems sound familiar to your business?
It is a known and familiar fact that businesses have to deal with such issues every day. Organizations of all sizes and needs are trying to find a solution and eliminate the bulk of such business problems.
Terms such as “cloud deployment” or “cloud computing” have been around for almost a decade, but the concept has recently started gaining popularity and momentum.
“To the cloud!” — Microsoft
We can understand the concept of ‘cloud’ by referring to it…
Named Entity Recognition (NER) is also known as “Entity Identification”. It is a Natural Language Processing (NLP) technique that seeks to locate and classify named entities mentioned in any form of unstructured text.
Each word is identified in predefined categories like Organization, Place, Person, Time Expressions, Quantities, Monetary Values, Percentages, etc.
Extraction of named entities from unstructured contextual data is beneficial for analyzing different types of textual data.
With tremendous advancements in NLP, machines are getting smarter. They can now intelligently understand large volumes of textual data that result in numerous use-cases like machine translation, text summarization, etc.
Intent Analysis is the process of determining the underlying intention behind any text or user-generated content in social networks.
But why is determining the expressed intents of customers and reviewers so important?
Well, any kind of written text, which may be a comment, review, feedback, or any other form of content, can provide deep insights into a customer’s requirements. It also lets us predict their next step, whether he/she wants to buy, sell, quit or recommend a product.
Understanding the intent behind a text can also help us classify the data quicker.
Here is an example:
“very confused… It keeps…
Manually looking through huge volumes of company database for a crucial piece of information can be highly time-consuming and practically impossible.
With the growing amount of data in recent years, it is difficult to obtain the relevant and desired information in a short period, especially during urgent matters.
In such cases, we can use Topic Modelling to mine through the data and fetch the information we are looking for quickly.
It automatically identifies topics present in a text object and derives hidden patterns exhibited by a text corpus. Thus, assisting better decision making.
A good topic model should result in…