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SMM Panorama
Seven Boats Info-System Pvt. Ltd. presents SMM Panorama Social media marketing tricks & hacks! made with Table of Contents 1. New Warning Alerts on Facebook for Fake News 2. Social Media Lessons to Learn from BuzzFeed 3. Social Influence Network: Do You Need It? 4. Your New Online Reputation Management Buddy: Facebook 5. Monetize Fan Frenzy on Facebook: Doing it Differently 6. The Rules of Getting Retweets on Twitter 7. Driving Facebook Traffic to your Website: Some Path-breaking Ways 8. Hashtags: What to Do with Them 9. Picking Influencers for Your Content 10. Facebook Engagement: How to Do it Best 11. Trivia to Make More from Twitter 12. Use Facebook Wisely for Content Marketing 13. Worry Less about Customers Engagement in Facebook 14. Thinking about B2B Social Media Strategy? Follow these 4 steps 15. Orange is the New Black: Social Media Lessons 16. Social Proofs: Why Have them and How 17. Facebook Lessons to Learn from Big Brands 18. Social Media Methods You Should Never Apply 19. 7 Tips to use social media in selling process 20. Make Use of Twitter Trends 21. Coming Up: New Video Metrics on Facebook 22. Video Marketing: Why to Bother; How to Prosper 23. A Few Social Media Mistakes that Can Cost Your Marketing Dear 24. Measuring Social Engagement Responsible for The Company’s Growth 25. How to Use Google+ for Business 26. Facebook or Twitter: More Value for your Ads 27. Want to Pull Up Twitter Popularity? Top 5 Tips to Do It! 28. Top Three Twitter Trackers 29. Social Media Metrics: What to Measure 30. -
Researching Candidates' Use of Twitter During the European Parliamentary Elections
11 Hailed by many as a game-changer in political communication, Twitter has made its way into election campaigns all around the world. The European Parliamentary elections, tak- ing place simultaneously in 28 countries, give us a unique comparative vision of the way the tool is used by candidates in different national contexts. This volume is the fruit of a research project bringing together scholars from 6 countries, specialised in communication science, media studies, linguistics and computer science. It seeks to characterise the way Twitter was used during the 2014 European election campaign, providing insights into communication styles and strategies observed in different languages and outlining meth- odological solutions for collecting and analysing political tweets in an electoral context. Tweets from the Campaign Trail the Campaign from Tweets Alex Frame / Arnaud Mercier / Gilles Brachotte / Caja Thimm (eds.) Tweets from the Campaign Trail Caja Thimm (eds.) · (eds.) Thimm Caja / Researching Candidates’ Use of Twitter During the European Parliamentary Elections Gilles Brachotte / Alex Frame is Associate Professor in Communication Science at the University of Burgundy (Dijon) where he works within the TIL research group (EA4182). Arnaud Mercier is Professor in Communication Science and member of the French Press Arnaud Mercier Institute (IFP, Paris). / Gilles Brachotte is Associate Professor in Communication Science at the University of Bur- gundy (Dijon) and member of the CIMEOS-3S research group (EA4177). Bonner Beiträge zur Medienwissenschaft Caja Thimm is Professor in Media Studies and Intermediality at the University of Bonn. Band 11 Alex Frame Alex BBM 11-Frame 267009_HOF_A5HCk-VH.indd 1 17.11.16 KW 46 12:48 11 Hailed by many as a game-changer in political communication, Twitter has made its way into election campaigns all around the world. -
Using Sentiment from Twitter Optimized by Genetic Algorithms to Predict the Stock Market Electical and Computer Engineering
Using Sentiment from Twitter optimized by Genetic Algorithms to Predict the Stock Market Carlos Vieira Simões Thesis to obtain the Master of Science Degree in Electical and Computer Engineering Supervisors: Prof. Rui Fuentecilla Maria Ferreira Neves Prof. Nuno Cavaco Gomes Horta Examination Committee Chairperson: Prof. António Manuel Raminhos Cordeiro Grilo Supervisor: Prof. Rui Fuentecilla Maria Ferreira Neves Member of the Committee: Prof. João Miguel Duarte Ascenso April 2017 Resumo Actualmente, na rede social Twitter, são criados, em media, cerca de 6000 tweets por segundo. Isto corresponde a cerca de 500 milhões de tweets por dia. Com toda esta informação torna-se interessante saber que partido se pode tirar dela. Neste trabalho propomos usar o Twiter para encontrar empresas que tenham um grande potencial de crescimento e que, por isso, sejam boas oportunidades de investimento. Para chegar a esse fim nós construímos um modelo de sentimento usando o texto contido em tweets. Para garantir que o nosso modelo de sentimento contém tweets que foram criados em contextos emocionais diferentes utilizámos hashtags do Twitter. Por exemplo, usámos as hashtags #sad e #happy para obter tweets que foram criados em ambientes emocionais distintos, ou seja, triste e feliz. Para nos certificarmos de que obtivemos tweets de um vasto leque de sentimentos usámos com permissão as emoções apresentadas pelo Circumplex Model of Affect e os seus sinónimos. São essas palavras que foram utilizadas como termos de pesquisa na API do Twitter. As emoções foram agrupadas em quatro classes. Por exemplo, emoções como feliz e orgulhoso foram incluídas na classe 1; calmo e sereno na classe 2; nervoso e ansioso na classe 3 e; triste e deprimido na classe 4.