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Media Content Analysis
 
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Hey guys! This is my term multimedia presentation on the course of Content Analysis : Introduction to Methodology Topic: Media Content Analysis. PLEASE, LIKE LIKE LIKE IT [even if you don't really do it :) ]
Views: 6452 Mariia Gorpynych
Media Content Analysis
 
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Immigrant and refugee health
Views: 1181 Amber May
Media Research - Content Analysis - Part 8
 
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This Lecture talks about Content Analysis.
Views: 1006 cec
Deep neural networks in social media content analysis - Adam Bielski
 
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Description How can we use the constantly growing number of photos and videos posted on social media? In this talk I will present three practical examples of deep neural networks applications to multimedia information extraction: logo detection, text extraction and popularity prediction. Abstract Every day large numbers of photos and videos are posted in social media. With the advent of modern deep learning, it is now possible to automatically analyze this content to get more in-depth insights. In this talk I will present three hands-on examples of how deep neural networks can be applied for social media content analysis. First, I'll present our neural network architecture used to detect logotypes in the videos given a limited amount of training data. Then I will show a working example of text-in-the-wild extraction (detection and recognition) pipeline. Last but not least, I'll show how video thumbnails can be used to predict video popularity. www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.
Views: 1173 PyData
Narrative Analysis in Media Studies
 
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A brief overview of how to analyse a media text. which is both engaging and informative. It can be used as a revision guide or as an introduction into narrative analysis.
Views: 43204 davesgud
Introduction to Media Literacy: Crash Course Media Literacy #1
 
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First thing’s first: what is media literacy? In our first episode, Jay breaks this question down and explains how we’re going to use it to explore our media saturated world. *** Resources & References: U.S. Adults Consume an Entire Hour More of Media Per Day Than They Did Just Last Year http://www.adweek.com/tv-video/us-adults-consume-entire-hour-more-media-day-they-did-just-last-year-172218/ Landmark Report: U.S. Teens Use an Average of Nine Hours of Media Per Day, Tweens Use Six Hours https://www.commonsensemedia.org/about-us/news/press-releases/landmark-report-us-teens-use-an-average-of-nine-hours-of-media-per-day NAMLE: Media Literacy Defined https://namle.net/publications/media-literacy-definitions/ *** Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/crashcourse Thanks to the following Patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Mark Brouwer, Nickie Miskell Jr., Jessica Wode, Eric Prestemon, Kathrin Benoit, Tom Trval, Jason Saslow, Nathan Taylor, Divonne Holmes à Court, Brian Thomas Gossett, Khaled El Shalakany, Indika Siriwardena, Robert Kunz, SR Foxley, Sam Ferguson, Yasenia Cruz, Daniel Baulig, Eric Koslow, Caleb Weeks, Tim Curwick, Evren Türkmenoğlu, Alexander Tamas, Justin Zingsheim, D.A. Noe, Shawn Arnold, mark austin, Ruth Perez, Malcolm Callis, Ken Penttinen, Advait Shinde, Cody Carpenter, Annamaria Herrera, William McGraw, Bader AlGhamdi, Vaso, Melissa Briski, Joey Quek, Andrei Krishkevich, Rachel Bright, Alex S, Mayumi Maeda, Kathy & Tim Philip, Montather, Jirat, Eric Kitchen, Moritz Schmidt, Ian Dundore, Chris Peters, Sandra Aft, Steve Marshall -- Want to find Crash Course elsewhere on the internet? Facebook - http://www.facebook.com/YouTubeCrashCourse Twitter - http://www.twitter.com/TheCrashCourse Tumblr - http://thecrashcourse.tumblr.com Support Crash Course on Patreon: http://patreon.com/crashcourse CC Kids: http://www.youtube.com/crashcoursekids
Views: 278393 CrashCourse
5 Facts on how to write a media analysis
 
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5 simple but useful tips on how to write an analysis for level 2 students.
Views: 7850 Carlyn Peever
Case Study -Analysis of e-Business Models for Digital Media Content
 
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Case Study Discussion of case title "Analysis of e-Business Models for Digital Media Content"
Web Analytics for Beginners - Presented by Bluehost
 
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[http://blue.host/EwsZ303GsQd] Tracking four basic metrics (total traffic, source of traffic, bounce rate, and conversion rate) can help small business owners fine-tune their web strategy and, ultimately, increase profits. There are countless things on your website that you can measure and analyze, but in this video, we focus on four key metrics for beginners. Total Traffic — The number of people visiting your site is a strong indicator of its overall health. This measurement can also help you identify what you’re doing right. For example, if you get a huge spike in traffic after publishing a guest post, you know your visitors liked the content. Source of Traffic — This measurement tells you how people are finding your website online. This can help you create a strategy going forward. If you find that most of your new visitors come for your social media posts, you’ll know that you should direct your efforts at creating more social content. Bounce Rate — A bounce is when a visitor leaves your site before clicking on another page. A high bounce rate can mean that the people coming to your site aren’t sticking around to make a purchase. This could be for a variety of reasons, including unappealing content, unattractive website design, or a hard-to-navigate menu. Conversion Rate — Conversion rate is the percentage of visitors who actually do what you’re asking them to do on your site, such as buy your product or subscribe to your blog. The higher your conversion rate, the better your site is doing. A low conversion rate can signal that your content and call to action are weak. Tracking web analytics does require time and effort, but carefully deciphering the data can lead to a more effective website — and more sales. VISIT THE BLUEHOST BLOG FOR MORE WEBSITE TIPS https://www.bluehost.com/blog/ SUBSCRIBE TO OUR CHANNEL https://www.youtube.com/subscription_center?add_user=bluehost CONNECT WITH US Facebook: https://www.facebook.com/bluehost Twitter: https://twitter.com/bluehost Google+: https://plus.google.com/+bluehost
Views: 42440 Bluehost
Narrated Media Content Analysis
 
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A content analysis project for my HEA 471 course of Immigrant and Refugee Health. This project enabled us to show others how the media alters our views of the news. Through this presentation I hope you all learn to do more analyzing before you believe what the media is telling you
Views: 23 Amaya McKoy
Research Methods 2 - Media Analysis & Visual Methods
 
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***Click the times below to jump to that part of the lecture*** 01:28 - Media Analysis: Framing 08:54 - Models for analyzing media 15:40 - Some examples of frame analyses 21:24 - Discourse Analysis 24:00 - Critical Discourse Analysis 27:38 - Visual Methods 47:44 - Some examples of photo elicitation and using maps 57:15 - (Even) More 'Out-there'
Views: 424 Jeroen Moes
Analysis of Social Media Content
 
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I created this video with the YouTube Video Editor (http://www.youtube.com/editor)
How to Set Up Media Assessment Content Analysis for Issues Management
 
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This video describes how to set up an issues management content analysis/media assessment using Google drive tools and the Lexis Nexus database.
Views: 53 Kathleen Sweetser
Web Content, Social Media Data Analysis & Digital Methods by Rachel Gibson and Kingsley Purdam
 
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Approaches to analysis of digital data for social science research. Focus is on both digitized methods those that have been adapted to the online environment and those that have been designed specifically for analysis of webcontent including social media data. For more methods resources see: http://www.methods.manchester.ac.uk
Views: 1238 methodsMcr
Analysing your Interviews
 
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This video is part of the University of Southampton, Southampton Education School, Digital Media Resources http://www.southampton.ac.uk/education http://www.southampton.ac.uk/~sesvideo/
Celine Marie Pascale-Qualitative Textual Analysis of Interviews and Media
 
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Presentation by Dr. Celine-Marie Pascale, from American University, as part of the webinar series on qualitative methodology. Title: Qualitative Textual Analysis of Interviews and Media.
The Top Social Media Competitor Analysis Tools & How to Use Them
 
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Social media is a fantastic tool to find competitors, analyze competitors, compare competitors and find out what they are doing, what’s working for them and what’s not so you can just model success instead of going through the slow process of trial and error. The other reason why it’s important to find competitors and analyze competitors is to make sure you are providing more or at least the same amount of value to your audience than they are. The first step when performing competitor research is to identify your 5 top competitors and look them up on the main social networks: Facebook, Twitter, Instagram and Linkedin. After your find competitors, collect the following information about them for each social network: Their audience size Their engagement rate Their engagement method Their posting frequency Their advantages Their disadvantages Once you’ve performed your competitor research and have collected enough information to compare competitors, you will have a clearer picture about how to improve your social media communication strategy. Then, to monitor your progress against your competitor’s progress and make sure you remain ahead, use social media competitor analysis tools depending on which platform you’re using. For example, should you have a Facebook page for your business and so do your competitors, we recommend using the built-in Facebook competitor analysis tool called “pages to watch”. This feature allows you to add any page you’d like to monitor against yours and easily compare competitors against you. The great thing about this competitor research tool is that your competitors won’t be notified that you’re monitoring them. Plus, this competitor research tool also suggests similar pages to watch. On Twitter, a tool to analyze competitors we recommend is Klout. Klout is a tool that gives you a score from 1 to 100 which rates a Twitter account’s social media influence. Most businesses have an average score of 40, however, influential accounts will have a score of 50 and above. Ideally, you’d like to have a higher Klout score than any of your competitors. Another social network analysis tool that is useful to analyze competitors is Twitter lists. Twitter lists are the equivalent of folders to categorize and manage Twitter accounts. Users can either create their own lists and make the lists “private” or “public’. Should you be using Twitter lists to monitor your competitors, make sure it is private so only you have the ability to view the list. This will allow you to check the activity of your competitors all in one place, see what they’re up to, what they’ve been tweeting, etc... and as a result improve your own social media communication strategy. When it comes to monitoring your competitors on Instagram, we recommend the social network analysis tool Talkwalker. Once you’ve collected all the information necessary that you need in order to have a clearer picture of where you stand compared to your competitors, don’t let that information go to waste. Instead, fine tune your campaigns accordingly. So you can remain one step ahead. The key when monitoring your competition and using social network analysis tools is not collecting too much information or else it’s easy to feel overwhelmed. Always improve your social media marketing efforts one step at a time.
Media Analysis of Social Media Post
 
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A media analysis of a social media post. Links to information regarding this video: https://www.washingtonpost.com/news/opinions/wp/2018/09/18/theres-overwhelming-evidence-that-the-criminal-justice-system-is-racist-heres-the-proof/?utm_term=.1ddbbc597d78 https://www.benjerry.com/home/whats-new/2016/systemic-racism-is-real https://mic.com/articles/129144/even-bill-o-reilly-is-calling-out-donald-trump-on-his-totally-wrong-racist-tweet#.oPjsgo2Nu https://www.factcheck.org/2015/11/trump-retweets-bogus-crime-graphic/ http://littlegreenfootballs.com/article/45291_We_Found_Where_Donald_Trumps_Black_Crimes_Graphic_Came_From
Views: 188 Douglas Wilson
Media Monitoring. Media Content Analysis. PR Research. Universitas Sebelas Maret.
 
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Anggota Kelompok 6 : 1. Nimas Dita Kusuma Dewi 2. Rastiti Hayu Utami 3. Rosita Sari 4. Syahwa
Views: 94 Syahwa Afidia
Content Analysis of Media Coverage of Childhood Obesity Topics in UAE Newspapers
 
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Comments: This videocast has been prepared by the International Journal of Health Policy and Management (IJHPM) Editorial Office www.ijhpm.com Contributing artists: Akram Khayatzadeh-Mahani, Fatemeh Yazdizadeh, Sahar Najafizadeh Speaker: Niyi Awofeso Mixed by: Hossein PourTavakoli Title of paper: Content Analysis of Media Coverage of Childhood Obesity Topics in UAE Newspapers and Popular Social Media Platforms, 2014-2017 Authors: Niyi Awofeso; Sara Al Imam; Arwa Ahmed School of Health and Environmental Studies, Hamdan Bin Mohammed Smart University, Dubai, UAE Article URL: http://www.ijhpm.com/article_3565.html DOI: 10.15171/ijhpm.2018.100 Copyright: © 2019 The Author(s); Published by Kerman University of Medical Sciences. This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/ by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Type: MP4 Length: 3:47
Views: 27 IJHPM Journal
Reputations Tip of the Day - Conduct Media Content Analysis
 
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Crisis communications consultant, Linda Bilben, shares tips and best-practices on crisis communications management and planning. Post-crisis tip #2: Analyze media coverage and communications for tone and key messages to determine what the impact might be on your reputation.
Views: 192 ReputationsCorp
Media Contents Analysis
 
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Media Contents Analysis
Views: 5 Jenn Paek
Social Media Analysis - Why you need an Analyst
 
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Why do people use Social Media and how can your business engage your customers successfully on Social Media? Copyright Social Media Analysis Ltd 2013
Media studies - textual analysis
 
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This is my media textual analysis for the main task
Views: 612 Alex Rayner
How To Write Media Analysis Essay
 
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#MediaAnalysisEssay #MediaAnalysisEssayExample #MediaAnalysisExample #ExamplesOfAnalysisEssays What is Media Analysis and how to cope with such task? The answer to this question you can get after reading our tips fot those who need to write a successful Media Analysis Essay https://best-writing-service.net/guide-to-writing-media-analysis.html
Deep Learning Integration for Alfresco Media Content Analysis (Images & Videos)
 
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This is the first of a video collection related to Venzia DeepLearning Server integration with Alfresco. In this series we developed a media content classification service, for Images and Videos!.
Views: 286 Venzia Spain
How Content Fuels Social Media: Content Gap Analysis
 
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How Content Fuels Social Media (June 15, 2016): You know your customer and you have your content ready to launch to target them, but are you missing something? Heather Timmerman and Sara Gomach Peck share on what a content gap analysis is and how you use it to find the holes in your content. Learn more about Sara & Heather of Acumium here: http://www.acumium.com/ Learn more about our monthly events here: http://www.SMBMad.org Twitter: http://www.twitter.com/SMBMAD Facebook: http://www.facebook.com/smbmad
Media content-analysis  (Контент-аналітичне дослідження медіа)
 
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Робота з курсу " Контент-аналіз: вступ до методології", НаУКМА, кафедра соціології.
Views: 145 Anastasiia Kurdydyk
Social Media Influencers Detection, Analysis & Recommendation Petr Podrouzek & Jan Rus-Socialbakers
 
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In the last years, social media (mainly Instagram) influencers gained immense popularity as more and more brands understand their potential for marketing products and services. The challenge is to recommend influencer(s) for a particular marketing campaign. Companies might be interested in micro influencers for a certain industry/region and they would also like to understand which content works for the audience of a particular influencer. After finding the right influencers they might want to start a marketing campaign with them and monitor the efficiency of such a campaign. In Socialbakers, we started tackling this problem in November 2018 when we piloted whether we can source Instagram’s business profiles and detect relevant attributes from those profiles. We processed large amounts of semi-structured data (1 TB) and tried to estimate demographic, geographic data and interests of each influencer. After that, we built a smart search algorithm that would take into account these attributes as well as various metrics. Finally, we designed a machine learning based recommender that links content with the influencers based on their audience. This content would serve as an inspiration to the campaign manager. The data exploration and prototyping were done in Databricks (pyspark). Final optimized ETL that processes the data and persists results in S3 and Elasticsearch was also built in Databricks. The content recommended utilizes NLP and other ML approaches. We had no knowledge of Apache Spark before the project so had to onboard the technology during the project. In this paper, we would like to discuss two aspects of the influencers project. Firstly, it is the final influencer recommendation solution where we used Databricks for innovative research and large-scale data engineering including ML. Secondly, it is the challenges we faced while deploying Apache Spark from the scratch and onboarding the teams to our new platform.
Views: 354 Databricks
Real-time Media Analysis
 
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Our flagship platform makes it easy to immediately collect, analyze and share television, digital and social media content surrounding your brand. This award-winning technology allows marketers to research media impact on the fly so that you can spend more time planning your next move.
Views: 228 iQ Media
Qualitative Analysis of Social Media
 
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AYUSH PAREEK (14UCS028)
Views: 811 ayushpareek

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