IR14 Pre-Conference Workshop Lightning Talk: Social Media Methods &amp; Ethics

This document contains a grocery shopping list with predicted prices and space to fill in actual prices found during a visit to a specific grocery store. It asks the student to reflect on whether they had enough money according to their budget, if any quantities demanded changed based on real prices, which goods fall under different market structures, which prices surprised them and why, how comparison shopping may impact future buying habits, and how demands may change and substitutions be made if shopping for a child.

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Jhon Jairo

Shut down point and profit

The document summarizes key concepts relating to firms operating in competitive markets including: - The four basic market types are perfect competition, monopolistic competition, oligopoly, and monopoly. - For a competitive firm, marginal revenue equals price since each additional unit sold does not impact the market price. - A competitive firm will produce the quantity where marginal revenue equals marginal cost to maximize profits. - In the short-run, a competitive firm will shut down if price falls below average variable cost. In the long-run, the firm will exit the market if price falls below average total cost.

Easy Data, Hard Data? Twitter Research and the Politics of Data Access

Extracting Important Information from Social Network Stream During Crisis

Avijit Paul

1) The document discusses a project that aims to extract important information from social media streams during crises to help with disaster management efforts. 2) The first 24 hours after a natural disaster are most crucial, but getting accurate information is difficult, making it hard to respond effectively. The project seeks to address this by filtering social media data to find actionable information that can help reduce harm and save lives. 3) The methodology involves analyzing tweets from 2011 Queensland floods to identify important tweets based on elements like named locations, images, and keywords. Different combinations of these elements are weighted to prioritize potentially useful information for emergency responders.

Cumulative and Comparative Social Media Analytics for Crisis Communication

This document discusses methods for analyzing social media data related to crisis events. It examines the use of Twitter data and application programming interfaces to study activity volume, key actors, and discussion themes during crises. The authors propose comparative and cumulative approaches to analyzing multiple crisis events over different locations and time periods to understand how crisis response systems evolve. Several case studies are presented comparing social media usage patterns for Queensland flooding in 2011 and 2013 and earthquakes in New Zealand in 2011 and 2013.

Researching Social Media in Times of Crisis

This document summarizes research on using social media for crisis communication. It discusses how different platforms like Twitter, Facebook, and Flickr are used to share information and media during crises. The challenges of disseminating and discovering information on social media during emergencies are also outlined. Case studies of the 2011 Queensland floods in Australia and the 2011 Christchurch earthquake in New Zealand demonstrate how social media can help distribute updates and self-organize relief efforts. The research aims to develop better analysis of social media patterns to evaluate communication strategies and support crisis response.

Social Media in Times of Crisis: The Australian Perspective

This document summarizes Associate Professor Axel Bruns' research on social media use during crises in Australia. It discusses two projects analyzing crisis communication - one focusing on the 2011 Queensland floods and another on detecting crisis events in social media. During the 2011 floods, the #qldfloods community rapidly organized online to share information. Emergency services also began adopting social media, though without clear strategies. The document outlines challenges in using social media for crisis information dissemination and discovery, such as identifying emerging events and evaluating information sources.

Analysing Twitter Activity in Crisis Contexts

This document analyzes Twitter activity during crisis contexts like floods and earthquakes. It finds that Twitter provided first-hand information and photos during crises. Communities formed around hashtags like #QLDFloods and #EQNZ to share updates and organize relief efforts. Analysis of these hashtags revealed changing patterns in retweets and mentions of emergency services and media over time, from rescue to recovery phases. The document advocates for better social media crisis communication strategies and tools to monitor issues and improve response.

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Social Media and Crisis Communication

This document discusses the use of social media, particularly Twitter, during crises and emergencies. It provides examples from the 2011 Queensland floods in Australia and the 2010-2011 earthquakes in Christchurch, New Zealand. Key findings include that Twitter allows for rapid sharing of first-hand information; different platforms are suited to different communication needs; and social media can help with community self-organization and resilience during crises. The document advocates analyzing social media communication patterns to improve emergency response strategies.

Shut down price

tutor2u

The document discusses shut down price and normal profit price for a firm operating in a perfectly competitive market. It shows these prices on a diagram with marginal cost, average cost and average variable cost curves. The shut down price is where price equals minimum average variable cost, as below this price the firm would face losses by continuing operations. The normal profit price is where price equals average cost, allowing the firm to cover total costs and earn normal profits in the short run. The shut down price is a short run concept that determines whether a firm should continue or cease production temporarily.

Hashtag as hybrid forum: the case of #agchatoz

Breakeven and shutdown

Chris Bell

The document discusses the concepts of breakeven point and shutdown point for firms. [1] The breakeven point is where a firm's total revenue equals its total costs, meaning it is covering all its economic costs and earning a normal profit. [2] The shutdown point is where a firm receives a price lower than its variable costs, so it should stop producing because it cannot even cover those costs. [3] Examples using diagrams illustrate how to determine breakeven and shutdown points based on the intersections of price, average total cost, and average variable cost curves.

Slicing Big Data: Gambling, Twitter & Time Sensitive Information

Netflix: Amazon S3 & Amazon Elastic MapReduce to Monitor at Gigascale (BDT302...

Amazon Web Services

How does Netflix stay on top of the operations of its Internet service with millions of users and billions of metrics? With Atlas, its own massively distributed, large-scale monitoring system. Come learn how Netflix built Atlas with multiple processing pipelines using Amazon S3 and Amazon EMR to provide low-latency access to billions of metrics while supporting query-time aggregation along multiple dimensions.

Treasure Data Cloud Strategy

Treasure Data, Inc.

Treasure Data is a cloud-based big data analytics company based in Silicon Valley with about 20 employees. The document discusses Treasure Data's services and architecture, which includes collecting data from various sources using Fluentd, storing the data in a columnar format on AWS S3, and performing analytics using Hadoop and SQL queries. Treasure Data aims to simplify big data adoption through its fully-managed platform and quick setup process. Example customers discussed were able to see results within 2 weeks of signing up.

Cosi Usage Data

daveyp

This document summarizes a presentation about collecting and analyzing library usage data and sharing it openly. The presentation discusses the types of data libraries collect, including circulation transactions, search queries, and e-resource usage. It shows examples of visualizing and analyzing the data. It also explains how the University of Huddersfield released two million circulation transactions as open data under Creative Commons, and the potential benefits of further sharing data between libraries. Barriers to sharing data between institutions and benefits of doing so are discussed.

Netflix presentation final

George Roth

Recognos is a semantic technology company established in 1999 with offices in California and Romania. They have 70 employees conducting research and development into semantic technologies. Their applications include finance, CRM, life sciences, and more. Semantic technology aims to teach machines human reasoning by representing knowledge as statements describing concepts, logic, and relationships. This allows for integrated querying across structured and unstructured data sources. Recognos can help companies like Netflix develop semantic applications such as integrated search across data sources and detecting similarities in film descriptions.

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This document discusses big data in the context of the web. It covers topics such as the characteristics of big data including volume, variety, velocity, veracity, and value. It discusses how the web represents a large source of diverse public data for analysis. It also discusses challenges related to big data like scalability, noise, bias, sparsity, and privacy. Examples are provided of analyzing large web data sources like Flickr photos, Wikipedia, and search engine query logs to gain insights.

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Big data in the web

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This document discusses big data in the context of the web. It covers topics such as the volume, variety, and velocity of big data; how the wisdom of crowds can be leveraged through data aggregation; challenges like sparsity, noise, and privacy; and examples of mining web data through techniques like clustering pictures on Flickr and analyzing click distributions. The document emphasizes that data must address important problems and proposes focusing on problem-driven approaches to analyzing large, diverse web data.

Lecture the dynamic web (2013)

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The document provides a history of the evolution of the World Wide Web from its origins in the late 1950s to the present day. It describes some of the key technological developments and innovations that have shaped the web over time, including the creation of ARPANET in the 1960s, the introduction of the first web browser in the early 1990s, the dot-com boom and bust of the late 1990s, and the rise of Web 2.0 applications in the 2000s. It also discusses how the needs and expectations of web users have changed, driving a shift from static websites to more dynamic websites that can efficiently support large volumes of frequently updated content from many sources.

BUILDING A SCALABLE MULTIMEDIA WEB OBSERVATORY

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Web and Internet Science research group seminar series. University of Southampton. 13th March 2013. The web is inherently multimedia in nature, and contains data and information in many different audio, visual and textual forms. To fully understand the nature of the web and the information contained within it, it is necessary to harness all modalities of data. Within the EU funded ARCOMEM project, we are building a platform for crawling and analysing samples of web and social-web data at scale. Whilst the project is ostensibly about issues related to intelligent web-archiving, the ARCOMEM software has features that make it ideal for use as a platform for a scalable Multimedia Web Observatory. This talk will describe the ARCOMEM approach from data harvesting through to detailed content analysis and demonstrate how this approach relates to a multimedia web observatory. In addition to describing the overall framework, I'll show some of the research aspects of the system related specifically to multimodal multimedia data in small (>100GB) to medium-scale (multi-terabyte) web archives, and demonstrate how these are targeted to our Parliamentarian and Journalist end-users.

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Linked Open Data in Libraries, Archives & Museums

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This document provides an overview of Linked Open Data for libraries, archives, and museums. It discusses the growing movement of LODLAM and how it allows these cultural institutions to represent their data as graphs using triples that describe entities in a machine-readable format. Key concepts covered include the use of URIs, RDF, vocabularies, and different legal tools for publishing open data.

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Introduction to big data

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This document summarizes an introduction to big data presentation. It defines big data as high volume, velocity, and variety of structured and unstructured data. It provides examples of how companies like Facebook and Target use big data analytics to gain insights into user preferences. The document also discusses technologies like Hadoop, Spark, and NoSQL that help process and analyze large datasets. Finally, it notes that the future is bright for big data due to growing data sources, improved processing abilities, and the ability to extract valuable insights from big data.

Scraping talk public

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1. The document discusses various methods for collecting data from websites, including scraping, using APIs, and contacting site owners. It provides examples of projects that used different techniques. 2. Scraping involves programmatically extracting structured data from websites and can be complicated due to legal and ethical issues. APIs provide a safer alternative as long as rate limits are respected. 3. The document provides tips for scraping courteously and effectively, avoiding burdening websites. It also covers common scraping challenges and potential workarounds or alternatives like using APIs or contracting data collection.

Think Big - How to Design a Big Data Information Architecture

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