Sentiment Analysis Services for NLP Projects
Help AI to identify and analyze the emotional tone of a written text. Determine whether the emotion is positive, negative, or neutral. Our sentiment analysis services cover vast ranges of texts including customer reviews on social media, emails, and even customer support chat system, etc
25,000+
Projects
9+ years
Experience
ISO
Certified
15,000+
Satisfied Clients
99.99%
Accuracy
Annotate Emotions of the Texts
If you’re an AI development company and looking for bulk data to feed your ML model, then we have something to offer you.
Visually represent customers’ opinions & sentiments about a company or product. Our sentiment analysis services can help your AI/ML model in analyzing text data. We’ll supply your model with a variety of feedback text, collected from social media, customer reviews, newspapers, questionnaires, and so forth. Our expert professionals assess sentiments from unstructured text documents and annotate the data.
Why sentiment analysis
Brief about Sentiment Analysis
Analyze sentiments into 3 major categories; positive, Negative, and Neutral
Further, the text can be broken into more emotional categories like joy, love, happiness, laughter, sadness, etc.
Multifaceted Analyses
Help ML models visualize textual data in different angles to develop a language-based AI system. We collect textual data from multiple sources including social media for the annotation task.
Moral Analysis
Analyze and visualize text data, categorize keywords as per the moral foundations
care
Fair
Authority
Ingroup
Purity
Where We Stand Little More Sophisticated
Explore here our in-demand services needs. What we offer as document management solutions is to create, store, organize, manipulate, and update documents. Here, we aim to digitize all your paperwork and make your office paperless with our dynamic solutions. Our broad and popular services in this vertical cover the following aspects;
Nuanced sentiment detection
Understanding texts and connecting them with human emotions is more than a complex job. BUT, at InputiX, we like to make complex and complicated tasks easy. For us, detecting nuanced sentiments is just a piece of cake. Not Joking! See how..
Sarcasm Detection
Often people express negative sentiment with a mix of sarcasm to make it look positive. Humans can understand that but for ML models to detect, they need advanced sentiment analysis. Gladly speaking, we do sarcasm detection where we comprehend the language and perform the contextual analysis.
Ambiguous Text Detection
Random text like chat can have subjective interpretation. To build a powerful text-processing application, sentiment analysis for ambiguous text is very important. Since it’s a complicated task; but our team is efficient enough to do it perfectly. We attach sentiment to each ambiguous text.
Detect Emoticons & Emojis
Emoticons and emojis are hugely popular across different social media platforms to convey sentiments. People often describe their sentiments using just a single emoji or emoticon. So, we help AI bots to understand the contextual meaning of the emoji or emoticons and express sentiments as outcomes.
Let us help you…
Accurately label text data to run sentiment analysis
Sentiment analysis is a human tendency as we can detect the emotions behind words. But machines cannot. With textual sentiment analysis, now AI models can detect non-verbal sentiments. To detect human emotion, AI/ML models need annotated data. Not just a few sets of data but a wide spectrum of data. From social media comments to Google reviews, textual data is the ultimate need here. While you develop your AI/ML model with sentiment analysis, let us help you with quality textual annotation data. We are a data annotation outsourcing service provider and we can handle bulk textual data annotation tasks. Our expert professionals assess sentiments from unstructured text documents and annotate the data. Category of sentiment analysis we perform;
Rule-based Assessment
We set sentiment rules based on the project requirement under rule-based sentiment assessment. In this assessment, we try to segregate nuanced emotions (amused, excited, jealous, etc) through textual data assessment.
Automatic Assessment
Some Python open-source toolkits can perform sentiment assessment but at the binary level. It means they can perform basic emotional assessments by scanning the text. At the basic NLP model, this model works. However, to build the best language-based model, you need something more strong and dense.
Hybrid Assessment
Integration of both, rule-based linguistics model plus automated sentiment analysis generates hybrid assessment. It annotates sentiments from a semantic perspective.
How We Perform Sentiment Analysis?
To build a powerful Natural Language Processing or NLP-enabled AI model, we annotate textual data in the following order.
1
Split Text Data
Segregate text documents into different basic components like paragraphs, phrases, sentences, words, and importantly, grammatical analysis.
2
Identify Sentiments
Each phrase is identified with each set of sentiment
3
Add Sentiment Score
Starting from -1 to +1 as a sentiment score getting assigned to each part of the phrase or text competent as whole.
Client Experiences
We find managing a lot of import-export documents by following all rules and regulations very difficult. Therefore, we wanted to have an outsourcing partner that could perform all document management tasks for us. Eventually, we found InputiX is very promising in their document management services. They organized all our documents in their respective folders within a specific period and handed all folders to us before the deadline.
Charles K., Director of a Broker Agency
Frequently Asked Questions (FAQ)
Let’s Start a Sentiment Analysis Demo Project Now!
Quickly brief us on your details to initiate a pilot sentiment analysis project with us.
Complete the form to set up a quick call (not more than 30 minutes) with our experts. They will guide you with the best advice for text annotation and sentiment analysis in detail. Don’t worry about the call, it’s a complementary gift (no payment) for medium and small businesses.
