A method for managing operations on data presented on a display of an electronic device, the method comprising: detecting data presented on a display of the electronic device; determining reading parameters associated with the data; performing a plurality of operations based on the reading parameters, wherein the reading parameters comprises at least one of a complete screen reading time taken by a user to completely read the data presented on the display of the electronic device, a partial screen reading time taken by the user to read at least one portion of the data, a scroll distance per one scrolling action on the display, or a data reading time which is a time taken to completely read the data presented on the display; wherein the determining of the reading parameters are performed based a plurality of machine learning, ML, regression models, wherein the plurality of ML regression models are trained by dividing a screen of the display of the electronic device into a plurality of blocks; extracting features of the data for each of the plurality of blocks; generating a first training dataset comprising an actual time taken to completely read the data presented on the display, the extracted features per each of the plurality of blocks, and a context of the data; generating a second training dataset comprising an actual scroll distance, the extracted features per each of the plurality of blocks, and the context of the data; training a first ML regression model from the plurality of ML regression models using the first training set to determine the complete screen reading time; and training a second ML regression model from the plurality of ML regression models using the second training dataset to determine the scroll distance per one scrolling action; the method further comprising: determining the scroll distance per one scrolling action based on the trained second ML regression model; and wherein one of the plurality of operations is performing a scroll the display based on the determined scroll distance per one scrolling action. detecting data presented on a display of the electronic device; determining reading parameters associated with the data; performing a plurality of operations based on the reading parameters, wherein the reading parameters comprises at least one of a complete screen reading time taken by a user to completely read the data presented on the display of the electronic device, a partial screen reading time taken by the user to read at least one portion of the data, a scroll distance per one scrolling action on the display, or a data reading time which is a time taken to completely read the data presented on the display; wherein the determining of the reading parameters are performed based a plurality of machine learning, ML, regression models, wherein the plurality of ML regression models are trained by dividing a screen of the display of the electronic device into a plurality of blocks; extracting features of the data for each of the plurality of blocks; generating a first training dataset comprising an actual time taken to completely read the data presented on the display, the extracted features per each of the plurality of blocks, and a context of the data; generating a second training dataset comprising an actual scroll distance, the extracted features per each of the plurality of blocks, and the context of the data; training a first ML regression model from the plurality of ML regression models using the first training set to determine the complete screen reading time; and training a second ML regression model from the plurality of ML regression models using the second training dataset to determine the scroll distance per one scrolling action; the method further comprising: determining the scroll distance per one scrolling action based on the trained second ML regression model; and wherein one of the plurality of operations is performing a scroll the display based on the determined scroll distance per one scrolling action.