Big data , Advanced Analytics and Social Sentiment Analytics
Musing the famous proverb “In God we trust. All others must bring data”, it’s apt to visualize a more connected and collaborative economy through the transparent and relevant information exchange. In today’s world, Artificial intelligence, Advances in Computing power and the Availability of Big Data are allowing Machine Learning algorithms to perform better and faster than ever. Social Media is becoming an important vehicle to reduce the digital divide as well as physical remoteness.
Newer opportunities are getting unfolded from the insights harnessed by Advance Analytical Models comprising of Machine Learning and Deep Learning. Social Sentiment Analytics is the computational study of people’s opinions, attitudes, and emotions toward an individual, event or topic by going through their posts, blogs, reviews, and opinions gathered from different social media web or mobile devices.
Natural Language Processing is an emerging field of Artificial Intelligence, which tries to read and interpret especially the unstructured data such as Text, to identify the sentiments, and then classify their polarity at different levels such as Document-level, Sentence-level, and Aspect-level, whichever is required.We help the organizations to build an end-to-end Social Sentiment Analytics Platform with an ability to understand the Underlying Mass sentiment about any person or object of interest as well as any likelihood of cluster formations with happy or disgruntled population. We help you to gather data from myriad sources such as
a) Local and International newspapers, b) Articles and blogs published in internet, c) Posts, tweets, Hash- Tags, Emoticons on social media.
In addition to that, we aid you to augment the Data quality and load them into a centralized Big Data Repository. The Data Ingestion, Cleaning and Big Data repository creation is done with several industry leading technologies such as Hadoop, PIG, HIVE, Spark, Flume, Kafka, MongoDB, PostgreSQL, Talend etc. as per the need of the solution. We assist you to decide the appropriate NLP technique in the process of extracting and selecting text features based on a) Measuring Terms Presence and Frequency, b) Tagging the Parts of speech tagging, c) Identifying root words, d) Recognizing Opinion words and phrases, e) Removing the stop words. We dedicate our time and effort to create a proper working dictionary (NLP Corpus) for your organizations to own. Our proposed model backed by suitable ML algorithm and the interactive visualization is all-set to keep your internal and external stakeholders thoroughly engaged.
Keeping the momentum with the latest technology trends, we use an entire gamut of Statistical and BI tools such as R, Python, Power BI, Tableau etc. We choose customized ML algorithms ranging from Supervised and Unsupervised to latest Reinforcement leaning. We design and deploy advance analytics methods comprising of Multivariate Statistics, Predictive Models, Time Series Forecasting, Naïve Bayes theorem, Recommender Systems, Support Vector Machine, Ensemble Trees and lately the Deep Learning with Artificial, Convolution and Recurrent Neural Network for Unstructured Data Mining, Text and Image Analytics. We are conversant with the several latest ML libraries, such as NLTK, Keras, H2O, Theano, Tensorflow, Lasagne etc.
Moreover, we propose and implement the right customized solution along with the optimum business models for organizations, considering their present infrastructure and future objective, strengthened by our expertise in leveraging the global technology trends and best practices.