Text Mining and Sentiment Analysis in Nepal

Marching Ants is equally exhilarated to offer text mining and sentiment analysis services by extracting data from Social media platform’s comments, reviews, blogs, mentions in online forums and transforming these data into insightful information. We use the best, standard and certified Text Mining tools to get accurate, efficient, and useful data, which are the attributes of a brand from the customer’s perspective.  

We provide a detailed research copy consisting of emotions and sentiments reflected by the text, especially positive, negative, and neutral. In cooperation with our clients, we provide scientific, systematic, and sustaining plans to eliminate all kinds of dissatisfaction shown by the consumers.


Insights will be revealed.

Every business has some raw text data about their either customer surveys, through maintenance logs, internal feedback or social media posts.These texts are the primary source to get information and statistics regarding the customer’s perception or behavior towards the brand. With  text mining services offered by Marching Ants, we help companies take action and respond quickly to the changing customer attitudes or areas of dissatisfaction.


Get to know the customers' voices.

Measuring public opinions and moods can be advantageous to your business. With text mining, you can assess how familiar or knowledgeable your customers are regarding your company's goals. Also, a deeper understanding of the product and its functionality can be obtained effortlessly with our text mining service.

Text mining helps you merge all of the customer's voices into one, enabling you to focus on problems that are bothering most of your customers. Fast and detailed text-mining by Marching Ants helps companies take action and respond quickly to the changing customer attitudes or areas of dissatisfaction.


Insight into the competitors’ work

Text Mining makes it possible to consume text-based reports and web pages produced by your competitors to understand their strategies and activities. This is necessary to comprehend emerging strategic trends needed for achieving a competitive edge in your niche industry.

You can get data on the customer-generated content and the textual information on their competitors’ social media sites. Further, transforming these data into knowledge would be a boon for decision-makers.


frequently asked questions

Online marketing's  90% of tasks or data are available by textual data found in social media networks or other online modes of communication. Thus, understanding the emotions hidden in these texts is crucial. For that, companies use Text mining, otherwise known as data mining. In Text Mining, unstructured text is transformed into a structured format to identify meaningful patterns and new insights.

Furthermore, companies use unstructured data to discover and analyze latent consumer relationships or experiences with their services or products. Not only that, text mining can be used to assess customer perceptions of your company to improve competitiveness. Text mining will help you understand the market environment and develop value-added strategies to compete with other companies.

Data from call center transcripts, online reviews, consumer surveys, and other text documents are gold mines when it comes to text mining. Various text mining tools have made it easy, quick, and efficient for businesses to analyze complex and large data sets, reducing some of their manual and repetitive tasks.


Text mining allows the analyst to hand-label cases with outcomes or classes to generate training data, while it requires an expert linguist to develop complex rule sets.

Text mining  is good at inductively creating models from historical data sets.On the contrary, Text Analytics has the potential to translate human comprehension into a set of linguistic laws.

Text analysis uses qualitative properties of a document or message (or a collection of documents) to extract text's salient characteristics. On other hand, text analytics is the fuel for quantitative approaches. data that is vital to the company.

When text analytics and text mining are combined, the results are always better and improved, as different views and strengths are integrated and disadvantages of one another are compensated.


In Text mining, we will deal with basically three types of data: Unstructured data, Semi-structured data, and Structured data.
Unstructured data:
There is no standard data format for this data. Text from websites such as social media or product reviews, video and audio files can all be used.
Semi-structured data:
This data is a mix of structured and unstructured data. It lacks the structure that a relational database needs. Email messages and images are good examples of semi-structured data.
Structured Data
Structured data is organized into a tabular format. This data is more convenient to store, process, and analyze. Accounting transactions, address descriptions, demographic information, customer feedback, location data are structured data.


Text mining allows you to extract useful information from unstructured data from various sources and identify and delete irregularities from data through cleaning operations. Further, your business can gain the following benefits:

Extract Meaningful Information from raw data
You can draw many important and relevant information regarding a specific topic by compressing the huge data with text mining. The type of data (unstructured/semi-structured) is also investigated. Furthermore, processing provides you with the knowledge that you need to make a specific decision.

Find out Patterns and behaviors.
Based on a specific collection of phrases/words, the extracted information will provide us with applicable and related customer behavior trends. Also, you can track and control user activity when retrieving relevant data.

Categorization and clustering
After gathering data from text documents, categorization is done. Here, data is processed and evaluated to find out suitable topics. Further, clustering is carried out. The text's intrinsic constructs are identified. Related "clusters" for further study are created within each group. Cluster analysis is the next step, and it is used to distribute data.

Set Grounds for personalized marketing
People(Audience) have become specific about their choices, whether it is their morning breakfast or the brands they want to purchase goods from. Thus, understanding audience feelings or expectations is essential for you to as a brand. With text mining, you can understand your consumer's/customers' textual data; you can deliver brand messages targeted to an individual prospect.