1. Articles in category: Sentiment

    49-72 of 764 « 1 2 3 4 5 6 ... 30 31 32 »
    1. Trump Tweets And Stock Sentiment

      Trump Tweets And Stock Sentiment

      Trump Tweets And Stock Sentiment Feb. 7, 2017 8:01 AM ET | How should investors react when President Trump tweets about a stock? Even the President of the United States suffers from "Diminishing Returns of Influence". Trump's tweets are a catalyst for a broader discussion which can be mined for insight. Source: BUZZ Indexes President Trump's inauguration hasn't slowed down his Twitter activity.

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    2. Automatic Construction and Global Optimization of a Multisentiment Lexicon.

      Automatic Construction and Global Optimization of a Multisentiment Lexicon.

      Automatic Construction and Global Optimization of a Multisentiment Lexicon.

      Comput Intell Neurosci. 2016;2016:2093406

      Authors: Yang X, Zhang Z, Zhang Z, Mo Y, Li L, Yu L, Zhu P

      Abstract Manual annotation of sentiment lexicons costs too much labor and time, and it is also difficult to get accurate quantification of emotional intensity. Besides, the excessive emphasis on one specific field has greatly limited the applicability of domain sentiment lexicons (Wang et al., 2010).

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      Mentions: Li L
    3. AI, Machine Learning and Sentiment Analysis Applied to Finance Seminar (London, United Kingdom - June 28-29, 2017) - Research and Markets

      By: Research and Markets via Business Wire News Releases January 31, 2017 at 11:38 AM EST AI, Machine Learning and Sentiment Analysis Applied to Finance Seminar (London, United Kingdom - June 28-29, 2017) - Research and Markets Research and Markets has announced the addition of the "AI, Machine Learning and Sentiment Analysis Applied to Finance" conference to their offering.

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    4. AI, Machine Learning and Sentiment Analysis Applied to Finance Seminar (London, United Kingdom - June 28-29, 2017) - Research and Markets

      AI, Machine Learning and Sentiment Analysis Applied to Finance Seminar (London, United Kingdom - June 28-29, 2017) - Research and Markets

      AI, Machine Learning and Sentiment Analysis Applied to Finance Seminar (London, United Kingdom - June 28-29, 2017) - Research and Markets Research and Markets has announced the addition of the "AI, Machine Learning and Sentiment Analysis Applied to Finance" conference to their offering. Technology innovations meet greatest success in business when these are entirely client focussed'.

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    5. Rezapour and Diesner to present sentiment analysis research at ICSC 2017

      Rezapour and Diesner to present sentiment analysis research at ICSC 2017

      » Rezapour and Diesner to present sentiment analysis research at ICSC 2017 Rezapour and Diesner to present sentiment analysis research at ICSC 2017 Posted: January 30, 2017 Assistant Professor » Doctoral student Shadi Rezapour and Assistant Professor Jana Diesner will present a paper at The 11th IEEE International Conference on Semantic Computing ( ICSC 2017 ), which will be held January 30 through February 1 in San Diego, California.

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    6. Sentiment Analysis Offers a Better Way to Conduct Polls

      Sentiment Analysis Offers a Better Way to Conduct Polls

      Anne Nasato Screenshot from estorm.org displaying Twitter sentiment in terms of political orientation. The majority of the polls for the 2016 Presidential Election turned out to be mistaken. One possible reason for this is that the majority of polls are based on survey questions. However, a group of engineering researchers may have found a better polling method by using the election to get an idea of popular opinion without resorting to survey questions.

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    7. Figuring out what Aussies think about Trump on Twitter is pretty difficult

      Figuring out what Aussies think about Trump on Twitter is pretty difficult

      Figuring out what Aussies think about Trump on Twitter is pretty difficult 783 Trump's election has been met with division, to say the least - but less so in Australia Image: Slate Scott Bingley, Paul Hawking for The Conversation 2017-01-22 07:00:01 UTC Follow @conversationuk Australians reacted more "positive" than "negative" to the election of Donald Trump as the next president of the United States, according to a sentiment analysis study of tweets that were posted at the time.

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    8. Optimized autocompletion of search field

      A computer receives event information associated with a user. The computer determines one or more social media contacts associated with the event, wherein the social media contacts are further associated with the user. The computer determines one or more terms utilized by the determined one or more social media contacts. The computer detects an input by the user, wherein the input includes one or more characters. The computer determines one or more autocomplete suggestions based on the one or more terms utilized by the determined one or more social media contacts.

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    9. Method and apparatus to calculate real-time customer satisfaction and loyalty metric using social media analytics

      A method and system are disclosed for providing a near-real-time measurement of sentiment and advocacy associated with user interactions within a social media environment. A first and second set of social media data, respectively associated with a first and second set of social media interactions, are processed to generate a first and second set of social network advocacy (SNA) data in near-real-time. The resulting first and second sets of SNA data are then processed to generate a first and second set of SNA Pulse (SNAP) metric data, which respectively indicate a near-real-time measurement of sentiment and advocacy for a given ...

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    10. Using social connection information to improve opinion mining: Identifying negative sentiment about HPV vaccines on Twitter.

      Using social connection information to improve opinion mining: Identifying negative sentiment about HPV vaccines on Twitter.

      Using social connection information to improve opinion mining: Identifying negative sentiment about HPV vaccines on Twitter.

      Stud Health Technol Inform. 2015;216:761-5

      Authors: Zhou X, Coiera E, Tsafnat G, Arachi D, Ong MS, Dunn AG

      Abstract The manner in which people preferentially interact with others like themselves suggests that information about social connections may be useful in the surveillance of opinions for public health purposes.

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    11. System and method for customized sentiment signal generation through machine learning based streaming text analytics

      Systems and methods may provide customized integrated indexes and visualization. Sentiment analytics may be based on natural language processing techniques. Users may select from among a range of indexes that reflect a variety of sources. Text scoring metrics or indices may incorporate frequency of mention, link to broker action, sentence location of first mention, etc. Depending on the temporal and sentiment characteristics of interest, the user may select from a range of news sources, research reports, analysts, social media sources, and may assign a customized weight value to each source. The scores may then be merged. After scoring, the user ...

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    12. Identifying key differences between related content from different mediums

      System, method, and computer program product to identify differences between different media formats of a media title, by identifying at least one component of each of the different media formats of the media title, the at least one component comprising a unit of the media title, annotating a respective text transcription of each of the different media formats of the media title to include at least one attribute of the respective at least one component, computing a difference score for a first component of a first media format of the media title relative to each of the remaining different media ...

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    13. Pyspark, Natural Language Processing(Sentimental Analysis), d3. by mambohayakuhusu

      Pyspark, Natural Language Processing(Sentimental Analysis), d3. by mambohayakuhusu

      Open Pyspark, Natural Language Processing(Sentimental Analysis), d3. This project is ending in 6 days and has an average bid price of $551 USD . 7 Project Description I have a project that needs developer who knows what they are doing. Here is the overview: 1. Collect tweets using tweeter streaming API, 2. Apply machine learning for sentimental analysis(NLP), (Apache spark is a must at this stage) 3.

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      Mentions: API
    14. These 19-Year-Old Engineering Students Predicted Trump's Win. Here's How.

      These 19-Year-Old Engineering Students Predicted Trump's Win. Here's How.

      These 19-Year-Old Engineering Students Predicted Trump's Win. Here's How. 2.8K Karis Hustad - Staff writer 11/9/16 @5:32pm in Education 11/9/16 @5:32pm While pollsters frantically changed their predictions as Donald Trump picked up Florida, Ohio, North Carolina (and eventually traditionally blue Wisconsin and Michigan), University of Illinois Urbana Champaign sophomores William Widjaja and Cody Pawlowski weren't surprised. They predicted he would win in June.

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    15. Message management method

      A method for managing computer based messaging involves monitoring messages transmitted within a messaging system over time; identifying related messages; and automatically analyzing the related messages using natural language analytics. The analyzing is based upon: subject of, sentiment within, and context of, each of the related messages, and frequency of transmittals of the related messages. The analyzing involves assigning at least: a first value based upon sentiment, a second value based upon content, and a third value based upon frequency, and calculating a score for the related messages as a function of the first value, second value and third value ...

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    16. #Ebook Deal/Day: Sentiment Analysis in Social Networks - $29.98 (Save 50%) Use code DEAL

      #Ebook Deal/Day: Sentiment Analysis in Social Networks - $29.98 (Save 50%) Use code DEAL

      Sentiment Analysis in Social Networks By Federico Pozzi, Elisabetta Fersini, Enza Messina, Bing Liu Publisher: Elsevier / Morgan Kaufmann Final Release Date: October 2016 Pages: 284 The aim of Sentiment Analysis is to define automatic tools able to extract subjective information from texts in natural language, such as opinions and sentiments, in order to create structured and actionable knowledge to be used by either a decision support system or a decision maker.

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    17. Hybrid human machine learning system and method

      Embodiments of the present invention provide a system, method, and article of hybrid human machine learning system with tagging and scoring techniques for sentiment magnitude scoring of textual passages. The combination of machine learning systems with data from human pooled language extraction techniques enable the present system to achieve high accuracy of human sentiment measurement and textual categorization of raw text, blog posts, and social media streams. This information can then be aggregated to provide brand and product strength analysis. A data processing module is configured to get streaming data and then tag the streaming data automatically using the machine ...

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    18. Configurable extractions in social media

      Disclosed are various embodiments for accessing and processing social media content. An extraction configuration comprising definitions for keywords, social networks, extraction times, and/or actions to be initiated upon a detection of a condition may be defined by a user of a site monitoring system. The defined social networks may be accessed at the defined extraction times to obtain data from a post comprising the defined keyword. The presence of some data in association with the post may initiate an action defined by the user.

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    49-72 of 764 « 1 2 3 4 5 6 ... 30 31 32 »
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