Challenges faced by Companies in Social Media Analytics

Social media has revolutionized the world & opening the new unexplored areas, which world has never seen earlier. Unethically defaming the products, services, organizations, celebrities, government policies, politicians, etc., has seen a drastic surge. Arab spring is a classic example of the shear strength of social media to uproot the decades of strong rule of dictatorship. However, the same logic is applied by extremists to motivate the innocent into wrongdoing. Social media analytics has hence become the powerful tool to bring to light these kinds of wrong doings. Social media has turned into a viral marketing platform to reach millions of customer in a short span of time. This poses another challenge to the companies in using advanced analytical tools to perform data mining & drawing meaningful business insights from unstructured data. Identifying each word used in the advertisement content contributes to it appearing in the social media when people search for their specific interests.

How will analytics solve these problems

Text Mining & Natural Language Processing are the social media analytical techniques, which are extensively used in drawing insights from unstructured data. Sentiment analysis is performed to identify the negative & positive things, which the world is speaking about various interests. Quick anomaly detection will help counter the outbreak of events, which cause severe harm. By making products smarter by avoiding features, which customer hate the most, organizations can become profitable. By analyzing the negative trend of brands, companies can avoid massive fiascos. By analyzing the hate comments, the radicalization of innocents can be avoided. By analyzing the data, support for political parties can be understood & corrective actions can be taken. By analyzing movie trends, sequels & prequels can be produced with better box office collections. By analyzing customer’s social media usage, better products/interests can be recommended & the list will go endlessly. In short, we all can live in a happy world with the right application of social media analytics.

Why Innodatatics?

Innodatatics, which is a startup company in analytics boasts of data science professionals & big data architects from top FT B-Schools & technology colleges. Also, we have a strong pool of Ph.D. professionals with thorough domain expertise, doing research on futuristic products & solutions. Word Clouds, Sentiment Analysis, Latent Dirichlet Allocation, Topic Extraction, Semantic Analysis, Network Analysis, NLP tools, Speech & Natural Processing, etc., are the text mining techniques in which Innodatatics has a strong control on. With the usage of open source tools, the price of implementing solutions would be extremely low & with world-class experts, the accuracy will be high & with the strong domain expertise business applicability of solutions is guaranteed.

Case Study 1 :   Want to know on how Sentiment Analysis is performed from Twitter’s unstructured data
Case Study 2 :   How risk sensing is performed on companies by extracting data from social media sites
Case Study 2 :   How risk sensing is performed on companies by extracting data from social media sites
Case Study 3 :   How to increase the probability of ‘click-through rate’ of ads posted on social media
Case Study 4 :   How to combine ‘Arcs & Emotion Mining’ for anomaly detection
Case Study 4 :   How to combine ‘Arcs & Emotion Mining’ for anomaly detection
Case Study 5 :   Analytics on Political party representatives