Abstract: A new approach is proposed that contemplates systems and methods to provide a comprehensive platform that enables a user to interactively measure, display, and analyze various characteristics of the social content items collected over a social media network in real time. The top content items, such as posts, links, photos, and videos that contains a set of query terms and are currently trending (mentioned frequently) or trending over a period of time are identified via various measurements and presented to a user. The user is then enabled to selectively and interactively view and analyze the content items presented based on the various metrics that unique to social media content items, such as the mentions (e.g., retweets) of the content items, the authors of the content items, and the spreading of the content items.

Abstract: A new approach is proposed that contemplates systems and methods to provide the ability to detect, measure, aggregate, and normalize sentiments expressed by a group of users on a certain event or topic on a social network so that the normalized sentiments truly reflect the sentiments of the general public on that specific event or topic. Additionally, the collected and measured sentiments of an individual user expressed on a social network can also be normalized against a baseline sentiment that reflects in order to truly reflect the individual user's sentiment at the time of his/her expression.

Abstract: A new approach is proposed that contemplates systems and methods to support efficient crawling of a social media network based on predicted future activities of each user on the social network. First, data related to a user's past activities on a social network are collected and a pattern of the user's past activities over time on the social network is established. Based on the established pattern on the user's past activities, predictions about the user's future activities on the social network can be established. Such predictions can then be used to determine the collection schedule—timing and frequency—to collect data on the user's activities for future crawling of the social network.