Microblogging

About: Microblogging is a research topic. Over the lifetime, 4186 publications have been published within this topic receiving 137030 citations. The topic is also known as: microblog.

Efficient Twitter sentiment classification using subjective distant supervision

Abstract: As microblogging services like Twitter are becoming more and more influential in today's globalized world, its facets like sentiment analysis are being extensively studied. We are no longer constrained by our own opinion. Others' opinions and sentiments play a huge role in shaping our perspective. In this paper, we build on previous works on Twitter sentiment analysis using Distant Supervision. The existing approach requires huge computation resource for analyzing large number of tweets. In this paper, we propose techniques to speed up the computation process for sentiment analysis. We use tweet subjectivity to select the right training samples. We also introduce the concept of EFWS (Effective Word Score) of a tweet that is derived from polarity scores of frequently used words, which is an additional heuristic that can be used to speed up the sentiment classification with standard machine learning algorithms. We performed our experiments using 1.6 million tweets. Experimental evaluations show that our proposed technique is more efficient and has higher accuracy compared to previously proposed methods. We achieve overall accuracies of around 80% (EFWS heuristic gives an accuracy around 85%) on a training dataset of 100K tweets, which is half the size of the dataset used for the baseline model. The accuracy of our proposed model is 2–3% higher than the baseline model, and the model effectively trains at twice the speed of the baseline model.

Geotagging twitter messages in crisis management

Abstract: All rights reserved. During times of crisis microblogging platforms such as Twitter have played an important role as a communication channel to distribute information. Particularly, disaster-related tweets are valuable resources when tagged with their location for detecting unexpected events. However, they often contain different types of location and one of the main challenges is resolving the ambiguity involved in their locations. The process of identifying phrase portions in unstructured texts with possible spatial aspects and disambiguating these references by linking them to geographic coordinates is known as Geotagging. In the context of crisis management, this paper presents OzCT geotagger that automatically detects the location(s) mentioned in the content of tweets with three possibilities: definite, ambiguous and no-location. It also semantically annotates the tweet components utilizing existing and new ontologies. The OzCT geotagger has been recently deployed in a trial system of the OzCrisisTracker application. Experiments demonstrate that the precision and recall for detection of the definite locations against geotagging by human judgement are on average of 80%. We also conclude that the accuracy of geographical focus of the OzCT geotagger is considerably higher than other systems. While existing geocoding systems have lower coverage for suburb and street focus, our approach detects suburbs in more than 60% situations.

Birds of a FETHR: open, decentralized micropublishing

Abstract: Microblogging, as exemplified by Twitter, is gaining popularity as a way to exchange short messages within social networks. However, the limitations of current microblog services--proprietary, centralized, and isolated-- threaten the long-term viability of this new medium. In this work we investigate the current state of microblogging and envision an open, distributed micropublishing service that addresses the weaknesses of today's systems. We draw on traces taken from Twitter to characterize the microblogging workload. Our proposal, fethr, connects micropublishers large and small in a single global network. New messages are gossiped among subscribers using a lightweight http-based protocol. Cryptographic measures protect authenticity and continuity of updates and prove message ordering even across providers.

CoffeeTweets: bonding around the bean on Twitter

Abstract: This chapter explores how we use social media to communicate our experience of the world and bond with others by forming communities of shared values. Microblogging services such as Twitter and Weibo are a form of social media allowing users to publish streams of length-delimited posts to internet-mediated audiences. As such they afford new kinds of interpersonal interaction via the conversation-like exchanges that occur (Honeycutt & Herring, 2009). An example of a length-delimited post (hereafter ‘micropost’) is the following. It contains one of the most common patterns in microblogging, an expression of thanks for personal endorsement: @Tim I love #coffee too This post is addressed to Tim using the @ symbol before the name, a construction which can also function as a reference to the person (e.g. @Tim makes great coffee), and contains a hashtag, the # symbol, which acts as a form of metadata labelling the topic of the post so that it can be found by others. This chapter will consider microposts such as this in terms of how they illuminate the way microblogging as a practice creates alignments around shared quotidian experiences by conferring upon the private realm of daily experience a public audience. The kind of personal expression of the everyday that we see in microposts has never been subject to real-time mass dissemination in the way that we are currently witnessing on Twitter. This chapter focuses on one such personal domain, coffeetalk, that is, discourse relating to coffee as consumed in everyday life.1 I will consider this discourse from two

Human dynamic model co-driven by interest and social identity in the MicroBlog community

Abstract: This paper analyzes the behavior of releasing messages in the MicroBlog community and presents a human dynamic model co-driven by interest and social identity. According to the empirical analysis and simulation results, the messaging interval distribution follows a power law, which is mainly influenced by the degree of users’ interests. Meanwhile, social identity plays a significant role regarding the change of interests and may slow down the decline of the latter. A positive correlation between social identity and numbers of comments or forwarding of messages is illustrated. Besides, the analysis of data for each 24 h reveals obvious differences between micro-blogging and website visits, email, instant communication, and the use of mobile phones, reflecting how people use small amounts of time via mobile Internet technology.