Hashtag Marbled Monday: A Webometric Analysis of Academic Special Collections Outreach on Instagram

This study used webometric analysis to assess the most successful strategies for engaging Instagram users in academic special collections. Data were collected from five academic special collections Instagram accounts to analyze their activity during the month of April 2018. Data considered in the study include average number of likes per post, average number of hashtags per post, and most common hashtags and content. The results of this analysis may serve as a recommendation for best practices for academic special collections interested in, or already using Instagram as a platform, to engage students and other Instagram users in their collections

Sentiment Analysis and Classifying Hashtags in Social Media Using Data Mining Techniques

Big data is one of the important topics which is still open for a wide range of applications for extracting useful information and knowledge for supporting organizations by planning and decision-making. Social media as a technology is an important resource of data, especially because it has been widely used in the last years. A Hashtag is recently one of the most popular features provided by Social media and is used by most social media users to express, share, and retrieve opinions and feelings regarding a specific theme. Hashtag features in social media are used more and more in recent years to discuss and debate important current events by public audience. This paper sheds light on how business can use such sources of information and how needed technical processes can be implemented accordingly. The paper demonstrates sentiment analysis as a scenario for such implementation. The main innovation in this paper is not limited to the technical method used, but rather to focus on the idea of using hashtags as information source in business, which is still rarely addressed in science. This paper will provide a novel model based on text mining techniques to provide a sentiment analysis for classifying business-related Hashtags posted on social media from the customers. The results will be presented and verified through samples of positive, and negative classified comments extracted from the Hashtags for supporting the organization by planning and decision making for generating completive advantages

eStorys: A visual storyboard system supporting back-channel communication for emergencies

This is the post-print version of the final paper published in Journal of Visual Languages & Computing. The published article is available from the link below. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. Copyright @ 2010 Elsevier B.V.In this paper we present a new web mashup system for helping people and professionals to retrieve information about emergencies and disasters. Today, the use of the web during emergencies, is confirmed by the employment of systems like Flickr, Twitter or Facebook as demonstrated in the cases of Hurricane Katrina, the July 7, 2005 London bombings, and the April 16, 2007 shootings at Virginia Polytechnic University. Many pieces of information are currently available on the web that can be useful for emergency purposes and range from messages on forums and blogs to georeferenced photos. We present here a system that, by mixing information available on the web, is able to help both people and emergency professionals in rapidly obtaining data on emergency situations by using multiple web channels. In this paper we introduce a visual system, providing a combination of tools that demonstrated to be effective in such emergency situations, such as spatio/temporal search features, recommendation and filtering tools, and storyboards. We demonstrated the efficacy of our system by means of an analytic evaluation (comparing it with others available on the web), an usability evaluation made by expert users (students adequately trained) and an experimental evaluation with 34 participants.Spanish Ministry of Science and Innovation and Universidad Carlos III de Madrid and Banco Santander

From a Tweet to the Street: The Effect of Social Media on Social Movement Theory

This thesis studies the role of social media within social movements and social movement theory and focuses on applying these theories to the Ni Una Menos movement of Argentina. I focus on three social movement theories: the resource mobilization theory, the political process theory, and the cultural approach. I also analyze the rise of social media in the 21st century and how they fit within the framework of the three theories. I then apply these theories to the Ni Una Menos movement. I argue that the Ni Una Menos movement emerged as a cultural movement, and shifted towards a resource mobilization movement and has only recently begun to fit the political process theory due to new laws and governmental plans. Social media is the main resource for this movement and is responsible for the formation and success of Ni Una Menos