TWITTER

New Search Strategies and Algorithms- Twitter

Table of Contents

Literature Review3

Research Questions/Hypothesis4

Methodology5

Contribution/Beneficiaries6

Research Planning and Scheduling6

References9

New Search Strategies and Algorithms- Twitter

Literature Review

With the growing information space on the Web and the increasing popularity of Social Media, Social Web applications became part of daily activities as well as the source of information for millions of people. (Zhao, 2009: 49) The dynamic nature of the Web and the diversity of the users along with the heavy information load demanded some form of adaptation or personalization in many Web-based applications in various domains. Nowadays, many Social Web applications are suffering from similar information overload problems, where the users of these applications find it difficult to read, find and follow the relevant and interesting information shared by a large network of other users. (Cha, 2010: 78) Our research will focuses on tackling information overload in one of the most popular of these applications, Twitter.

Twitter is the most popular micro-blogging site and a growing Social Web phenomenon that is attracting interest from different types of people all around the world for a variety of different purposes, such as fast communication, work, status updates, following news, sports, events, opinions, hot topics, and so on. (Kwak, 2010: 25) With millions of Twitter messages (tweets) per day, highly active users are estimated to receive hundreds of tweets every day". Due to the lack of any adaptive or personalized navigation support in Twitter, users may get lost, become de-motivated and frustrated in this network of information overload. Accessing required or interesting fresh content easily is vital in today's information age. (Cha, 2010; 136) Hence, there is a need for an effective personalized searching option from the users' point of view that would assist them in following the optimal path through a series of facets to find the information they are looking for, while providing a structured environment for relevant content exploring. Our research focuses on investigating ways to enhance searching and browsing in microblogging sites like Twitter by means of adaptive and personalized faceted search. (Hughes, 2009: 235)

Searching and browsing are, indeed, somewhat limited in Twitter. For example, one can search for tweets by a keyword or by a user in a timeline that would return the most recent posts. (Zhao, 2009: 144) So, if a user wants to see the different tweets about a field of sports, and were to search for "sports" in Twitter, only the recent tweets that contain the word "sports" would be listed to the user. Many tweets that do not contain the search keyword, but are about different sport events, sport games and sport news in general, would not be returned. Moreover, the Twitter keyword search differs from the general Web search due to the restricted message size of 140 characters in Twitter. (Cha, 2010: 163) Traditional faceted search interfaces allow users to search for items by specifying queries regarding different dimensions and properties of the items (facets. For example, online stores such as eBay or Amazon'' enable narrowing down their users' search for products ...