Sentiment Analysis (SA) has achieved significant growth in recent decades among the evolving applications, including social networks and decision-support systems. Recently, the proliferation of data volumes for Dravidian languages has made SA a significant task to retrieve useful information. The prevailing works are focused more on the monolingual analysis and lack a complete study of the recent trends. The research presents a survey on the evolving landscape of SA in Indian languages with a specific emphasis on Dravidian languages. An overview of SA, emphasizing the levels and the purpose of the analysis is presented. Moreover, the generic process is explained with the major advancements of pre-trained architectures applied in recent works. Along with the various classification methodologies, this study analyzes the strengths conforming to the various training databases and languages, mainly focused on sentiment classification. Furthermore, an exhaustive view of the existing challenges and the applications is provided, offering unique linguistic guidance in the field of SA.

There is enormous amount of data is available on the internet today in the agricultural domain. About the history of agricultural produce, type of seeds, the fertilizers used, Industrial agriculture, monoculture, agronomy, information on agrochemicals. Plants being grouped into Angiosperms, gymnosperms, perineal, non-perineal etc. In such situation the need for Information retrieval systems is high as the Questionnaires posted by the end user has to be rightly understood, and to provide accurate results with the available colossal data is at its peak. Multiclass classification of agricultural Pomegranate Questionnaire. This paper intends to discuss on the different types of algorithms that can be employed in the evaluation of the Pomegranate Questionnaire raised by the end user. Farmers, being the end user can request in the form of Questions regarding the name of the fruit, details such as the growing climatic conditions required, vitamins contents and mineral components crop growing fertilizers, suitable crop rotation techniques taking into consideration of climate, humidity, temperature, the soil of the region where he is residing etc. It proposes the different types of algorithms can be used for multi class question classification having classes i.e. Name, Descriptive, Numeric, Location and Entity: Other.