Iowa Public Television’s Planning Targets 2011-2014

Agency Performance Plan, Iowa Public Televisio

Detection of Hateful Comments on Social Media

Social media usage has grown tremendously in the contemporary communication landscape. Along with its numerous benefits, some users abuse the channels by spreading hatred, far from the intended purpose of building connections on a personal level. To date, an empirical method for detecting, quantifying, and categorizing hateful comments on social networks comprehensively and proactively is still lacking. Besides, majority of the cases remain unreported due to social confounders such as fear of victimization and the psychological implications of hateful comments, leading to a situation whereby, the detrimental effect of the situation is underestimated. The ill-defined situation in the growing online space impedes progress towards developing mechanisms and policies to mitigate the harmful effects of hate on social media, ultimately reducing the effectiveness of the platforms as effective communication tools. This proposal suggests Naïve Bayes classifier as a novel approach for detecting and classifying hateful social media comments to bridge this gap. Data set was taken from set provided by Kaggle and consisted of 30,000 Tweets. From the results of the use of this method, it was calculated that Bayes method is 62.75% accurate, which is not satisfactory. However, to bridge accuracy gap, nural algorithm was used which gain an improved accuracy of 87%

BlogForever D5.1: Design and Specification of Case Studies

This document presents the specification and design of six case studies for testing the BlogForever platform implementation process. The report explains the data collection plan where users of the repository will provide usability feedback through questionnaires as well as details of scalability analysis through the creation of specific log files analytics. The case studies will investigate the sustainability of the platform, that it meets potential users’ needs and that is has an important long term impact

"Too close to call" : CNN's politics of captions in the coverage of the Florida Recount

Proceeding chronologically in terms of the events covered, Raimund Schieß in his paper „Too close to call: CNN’s politics of captions in the coverage of the Florida Recount“ focusses on Nov. 11, 2000, when the Bush campaign applied to Miami Federal Court to stop the manual recount of ballots which had been started in some counties. The paper studies the discursive practices employed by the CNN journalists to construct a particular version of the events, focussing on captions, i.e. the lines of text inserted at the bottom of the tv screen, and on the way in which they interact with the other verbal and visual components of the television text. Raimund Schieß concludes that captions, far beyond providing mere details of a speech event (who is talking to whom about what, where and when), are used to select, to highlight and hide, and thus to invite a preferred interpretation of the event. He is also able to show that captions are often employed to exploit a story’s potential for drama and sensation. His detailed micro-analysis of the verbal and visual dimensions of the television text is supported by careful documentation of the data, either through screen shots or via transcriptions of the stretches of broadcast discussed

Enhancing Mental Health Awareness through Twitter Analysis: A Comparative Study of Machine Learning and Hybrid Deep Learning Techniques

This study explores the utilization of social media data, specifically tweets and comments, for gaining insights into individuals' mental health conditions. The objective is to enhance mental health awareness and enable early detection and intervention. Twitter data is collected using depression-related keywords, and two models are employed: a Random Forest model with TF-IDF and a hybrid CNN-LSTM model incorporating word2vec. The performance of the CNN-LSTM model surpasses that of the Random Forest model, achieving an accuracy rate of 89.4%. Furthermore, a user interface is developed to analyze users' Twitter profiles based on their tweets, allowing for potential intervention through automated reply messages. By harnessing social media data and advanced machine learning techniques, this research contributes to improving mental health awareness and timely addressing of mental health concerns

From Comunities of Practice to Epistemic Communities: Health Mobilizations on the Internet

This paper describes the emergence of new activist groups in the health sector, spinning off from internet discussion groups. In the first part, it shows how self-help discussion groups can be considered as communities of practice in which, partly thanks to the Internet media, collective learning activities result in the constitution of experiencial knowledge, the appropriation of exogenous sources of knowledge, including medical knoweldge and the articulation of these different sources of knowledge in some lay expertise. In the second part, it describes how activist groups might emerge from these discussion groups and develop specific modes of action drawing upon the forms of expertise constituted through the Internet groups. Activists groups together with self-help groups might form epistemic communities (Haas 1992), i.e. groups of experts engaged in a policy enterprise in which knowledge plays a major role : in the confrontation of health activists with professionals, the capacity to translate political claims into the langage of science appears as a condition to be (even) heard and be taken into consideration.Childbirth, Obstetrichs, Health, Internet, Discussion Groups, Activism, Epistemic Communities, Communities of Practice, Experiencial Knowledge, Scientific Knowledge

RFCs, MOOs, LMSs: Assorted Educational Devices\ud

This paper discusses implicit social consequences of four basic internet protocols. The results are then related to the field of computer-assisted teaching. An educational on-line community is described and compared to the emerging standard of web-based learning management.\u

A Survey on Cybercrime Using Social Media

There is growing interest in automating crime detection and prevention for large populations as a result of the increased usage of social media for victimization and criminal activities. This area is frequently researched due to its potential for enabling criminals to reach a large audience. While several studies have investigated specific crimes on social media, a comprehensive review paper that examines all types of social media crimes, their similarities, and detection methods is still lacking. The identification of similarities among crimes and detection methods can facilitate knowledge and data transfer across domains. The goal of this study is to collect a library of social media crimes and establish their connections using a crime taxonomy. The survey also identifies publicly accessible datasets and offers areas for additional study in this area

The impact of technology: value-added classroom practice: final report

This report extends Becta’s enquiries into the ways in which digital technologies are supporting learning. It looks in detail at the learning practices mediated by ICT in nine secondary schools in which ICT for learning is well embedded. The project proposes a broader perspective on the notion of ‘impact’ that is rather different from a number of previous studies investigating impact. Previous studies have been limited in that they have either focused on a single innovation or have reported on institutional level factors. However, in both cases this pays insufficient attention to the contexts of learning. In this project, the focus has been on the learning practices of the classroom and the contexts of ICT-supported learning. The study reports an analysis of 85 lesson logs, in which teachers recorded their use of space, digital technology and student outcomes in relation to student engagement and learning. The teachers who filled in the logs, as well as their schools’ senior managers, were interviewed as part of a ‘deep audit’ of ICT provision conducted over two days. One-hour follow-up interviews with the teachers were carried out after the teachers’ log activity. The aim of this was to obtain a broader contextualisation of their teaching

HiER 2015. Proceedings des 9. Hildesheimer Evaluierungs- und Retrievalworkshop

Die Digitalisierung formt unsere Informationsumwelten. Disruptive Technologien dringen verstärkt und immer schneller in unseren Alltag ein und verändern unser Informations- und Kommunikationsverhalten. Informationsmärkte wandeln sich. Der 9. Hildesheimer Evaluierungs- und Retrievalworkshop HIER 2015 thematisiert die Gestaltung und Evaluierung von Informationssystemen vor dem Hintergrund der sich beschleunigenden Digitalisierung. Im Fokus stehen die folgenden Themen: Digital Humanities, Internetsuche und Online Marketing, Information Seeking und nutzerzentrierte Entwicklung, E-Learning