Popularity of smartphones also popularized, reading content using smartphones. Reading using smartphones quite differs from reading using desktop system. Mouse and keyboard are the peripherals associated with the reading in desktop systems. Study of the handling of such devices has led to provide implicit feedback of the content read. Similar study in smartphones to get implicit feedback remains to be a huge gap. Reading using smartphones involves screen gestures like pinch to zoom, tap, scroll, orientation change, and screen capture. User reading behavior and intent can be inferred by screen gestures. Smartphones have sensors like gyroscope and accelerometer that continuously capture data without permissions from the users. To analyze screen gestures, a dataset has been created. Dataset is organized into accelerometer and gyroscope folders. This dataset can act as an input to train, test, and validate, machine learning models to analyze smartphone reading behavior and user intent.