Timeline Generation: Tracking individuals on Twitter

In this paper, we propose a unsupervised framework to reconstruct a person's life history by creating a chronological list for {\it personal important events} (PIE) of individuals based on the tweets they published. By analyzing individual tweet collections, we find that what are suitable for inclusion in the personal timeline should be tweets talking about personal (as opposed to public) and time-specific (as opposed to time-general) topics. To further extract these types of topics, we introduce a non-parametric multi-level Dirichlet Process model to recognize four types of tweets: personal time-specific (PersonTS), personal time-general (PersonTG), public time-specific (PublicTS) and public time-general (PublicTG) topics, which, in turn, are used for further personal event extraction and timeline generation. To the best of our knowledge, this is the first work focused on the generation of timeline for individuals from twitter data. For evaluation, we have built a new golden standard Timelines based on Twitter and Wikipedia that contain PIE related events from 20 {\it ordinary twitter users} and 20 {\it celebrities}. Experiments on real Twitter data quantitatively demonstrate the effectiveness of our approach

Leveraging Contextual Cues for Generating Basketball Highlights

The massive growth of sports videos has resulted in a need for automatic generation of sports highlights that are comparable in quality to the hand-edited highlights produced by broadcasters such as ESPN. Unlike previous works that mostly use audio-visual cues derived from the video, we propose an approach that additionally leverages contextual cues derived from the environment that the game is being played in. The contextual cues provide information about the excitement levels in the game, which can be ranked and selected to automatically produce high-quality basketball highlights. We introduce a new dataset of 25 NCAA games along with their play-by-play stats and the ground-truth excitement data for each basket. We explore the informativeness of five different cues derived from the video and from the environment through user studies. Our experiments show that for our study participants, the highlights produced by our system are comparable to the ones produced by ESPN for the same games.Comment: Proceedings of ACM Multimedia 201

“Shut Up and Dribble”

The National Basketball Association is first and foremost a company which tries to generate revenue. As such, the NBA is embedded into a system of mass media and thereby influenced by cultural, social, and political events. Simultaneously, the NBA can also (partly) cause such events. Lastly, the NBA (and professional basketball at large) has always featured a racial component. Thereby, the NBA features three key American concepts and/or conflicts (corporate interest, meritocracy, race) and, through critical as well as historically-oriented analysis, allows to grasp the interplay of these concepts, at least in a temporally and spatially defined context. This article discusses three individual cases in which the NBA had to react as a race-related image crisis doomed or, in other words: a representative of corporate America had to react to fractures appearing on its otherwise coherent and shiny outside caused by (implicitly or explicitly) racialized aspects. As such, the NBA can be read as a larger extension of American culture and life. In order to understand these three cases as well as the corporate responses in their specific context, the paper will start by providing an overview of professional basketball’s history with special consideration of racial aspects. This is followed by the illustration and critical discussion of the three cases and results in a short summary. The overarching focus of the paper is the question of what keeps the NBA – as a company plagued by racial fractures – together at heart. It is assumed that the NBA, as a proto-American sports league, is held together by the same unifying moments which keep America (at least partially) intact and running

Program

11th Annual Research and Engagement Day Program with descriptions and schedule of events

Predicting In-game Actions from Interviews of NBA Players

Sports competitions are widely researched in computer and social science, with the goal of understanding how players act under uncertainty. While there is an abundance of computational work on player metrics prediction based on past performance, very few attempts to incorporate out-of-game signals have been made. Specifically, it was previously unclear whether linguistic signals gathered from players' interviews can add information which does not appear in performance metrics. To bridge that gap, we define text classification tasks of predicting deviations from mean in NBA players' in-game actions, which are associated with strategic choices, player behavior and risk, using their choice of language prior to the game. We collected a dataset of transcripts from key NBA players' pre-game interviews and their in-game performance metrics, totalling in 5,226 interview-metric pairs. We design neural models for players' action prediction based on increasingly more complex aspects of the language signals in their open-ended interviews. Our models can make their predictions based on the textual signal alone, or on a combination with signals from past-performance metrics. Our text-based models outperform strong baselines trained on performance metrics only, demonstrating the importance of language usage for action prediction. Moreover, the models that employ both textual input and past-performance metrics produced the best results. Finally, as neural networks are notoriously difficult to interpret, we propose a method for gaining further insight into what our models have learned. Particularly, we present an LDA-based analysis, where we interpret model predictions in terms of correlated topics. We find that our best performing textual model is most associated with topics that are intuitively related to each prediction task and that better models yield higher correlation with more informative topics.Comment: First two authors contributed equally. To be published in the Computational Linguistics journal. Code is available at: https://github.com/nadavo/moo

Twitter\u27s Impact on Sports Journalism Practice: Where a New Medium Meets and Old Art

This project aims to determine if and how the relatively new journalistic tool of Twitter is impacting journalistic decision-making and news production as a legitimate tool amongst sports writers. Using the methods of qualitative textual analysis and in-depth interviewing, this project analyzes the words and tweets of nine journalists at prominent U.S. newspapers in an attempt to fill a void in research among the topics of journalistic decision-making, sports journalism, and Twitter and to answer questions that arise from the marriage of a certain type of journalism and a particular new media platform

Streaming Big Data Analysis for Real-Time Sentiment based Targeted Advertising

Big Data constituting from the information shared in the various social network sites have great relevance for research to be applied in diverse fields like marketing, politics, health or disaster management. Social network sites like Facebook and Twitter are now extensively used for conducting business, marketing products and services and collecting opinions and feedbacks regarding the same. Since data gathered from these sites regarding a product/brand are up-to-date and are mostly supplied voluntarily, it tends to be more realistic, massive and reflects the general public opinion. Its analysis on real time can lead to accurate insights and responding to the results sooner is undoubtedly advantageous than responding later.  In this paper, a cloud based system for real time targeted advertising based on tweet sentiment analysis is designed and implemented using the big data processing engine Apache Spark, utilizing its streaming library. Application is meant to promote cross selling and provide better customer support

Twitters Impact on Sports Media Relations

The introduction of Social Media (SM) into sports communications in professional leagues is disrupting the traditional methods of sports media relations. In the past, teams used websites to post information for fans, but it was strictly a one-way format of communication whereby a story was posted for fans to read. To fully engage with this new communication channel, the sports communications departments in professional leagues have begun to use SM to communicate directly with fans through platforms like Twitter and Facebook. Currently, SM like Twitter allows the team communication departments to communicate directly with fans in an interactive two-way format that is not mediated by a reporter or someone from a traditional media outlet. In addition, the open format of SM means that media relations staff are no longer the only intermediary between the media and the players; through the use of SM like Twitter, a professional athlete can now communicate directly to fans without gatekeepers like the media or the sports communications department of the team. This thesis will explore how SM has changed media relations from several different perspectives. The first perspective is related to the risks that are associated with the use of SM by professional athletes: without an intermediary or a filter for athlete-fan communication, many athletes have caused irreparable damage to their reputation and the reputation of their team. The second perspective is related to the benefits for teams that use SM as a platform to connect with fans: the ability to connect with fans using SM is new to sports communications and represents an interactive one-to-one and one-to-many mode of communication through which the fan can directly communicate with the team. Finally, this research will look at how Twitter has changed media relations in sports from the perspective of the lived experiences of people who work in sports media. To explore the risks associated with athletes’ use of social media, this research used Situational Crisis Communication Theory as a theoretical framework to explore reputation-damaging incidents that occurred through social media. The study reviewed national media stories reported in North America from 2009 to 2010 that were perceived to have negative impact on athletes’ reputation. In total, 17 incidents were reviewed — seven incidents in particular demonstrated the athlete as the source of the SM crisis. Through the review and categorization of these 17 situations, the study was able to identify four broad categories of situations that a sports communication manager needs to be prepared for. The four categories identified were “Rookie Reporter”, “Team Insider”, “Opportunist”, and “Imposter”. Each of these categories are invaluable for team communication managers to recognize in order to address the risks associated with social media. To explore the benefits associated with the communications department’s use of social media, this research used Uses and Gratification theory as a theoretical framework to explore how and why fans followed team Twitter accounts. This study was conducted in partnership with the Canadian Football League (CFL) and a total of 526 people responded to an online survey that was tweeted out to them for their feedback. The results of the survey indicated several significant findings — in particular, the phenomenon of converged sports fan consumption was identified, which has not been previously acknowledged in academic research. The phenomenon of converged sports fan refers to the multi-screen environment whereby a sports fan decides where, when, and how they want to consume sporting content. This research identified that in-game consumption of SM while watching television and the mobile consumption of SM are both dominant ways for fans to interact with their teams. This multi-modal format of connecting with the team supports the idea of Henry Jenkins’s Black Box Fallacy (2006, p. 13): as teams move forward in developing communications platforms to reach their fans, they will need to recognize that all channels can and do work together. In order to further understand how Twitter has changed sports media relations, the study used long semi-structured interviews with a phenomenological research design to understand how Twitter has impacted sports media relations. The phenomenological analysis of the informant interviews suggested that Twitter is the source of three themes of change: general media relations, mechanical job functions, and other changes specific to sports media relations. The significance of Twitter’s impact on sports media relations cannot be understated. With the ubiquitous use of SM like Twitter, it is important to understand how sports media relations can use SM to manage the image of their respective teams and athletes. After looking at SM and sports from three different perspectives, the pivotal finding was the role that Twitter and mobile communications play in ‘flattening’ sports media relations. Similar to how Friedman (2006) argued that the convergence of the personal computer drove globalization, Twitter and the increased adoption of mobile communications have flattened the role of sports media relations. This research will explain how the flattening of sports media relations happened and what the implications might be for sports media professionals