sentistrength.wlv.ac.uk Report : Visit Site


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    Server:Apache/2.4.7 (Ubuntu...

    The main IP address: 134.220.4.154,Your server United Kingdom,Wolverhampton ISP:University of Wolverhampton  TLD:uk CountryCode:GB

    The description :test - download - java version - non-english - buy! - about sentistrength automatic sentiment analysis of up to 16,000 social web texts per second with up to human level accuracy for english - other l...

    This report updates in 03-Jul-2018

Technical data of the sentistrength.wlv.ac.uk


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Latitude: 52.585468292236
Longitude: -2.1229600906372
Country: United Kingdom (GB)
City: Wolverhampton
Region: England
ISP: University of Wolverhampton

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Keep-Alive:timeout=5, max=100
Server:Apache/2.4.7 (Ubuntu)
Last-Modified:Wed, 27 Jun 2018 10:12:23 GMT
Connection:Keep-Alive
ETag:"bd4a-56f9cd9d16b78-gzip"
Date:Tue, 03 Jul 2018 09:57:16 GMT
Content-Type:text/html

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cname:csl-staff.wlv.ac.uk.
ipv4:IP:134.220.4.154
ASN:786
OWNER:JANET Jisc Services Limited, GB
Country:GB

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test - download - java version - non-english - buy! - about sentistrength automatic sentiment analysis of up to 16,000 social web texts per second with up to human level accuracy for english - other languages available or easily added. sentistrength estimates the strength of positive and negative sentiment in short texts , even for informal language. it has human-level accuracy for short social web texts in english, except political texts. sentistrength reports two sentiment strengths: -1 (not negative) to -5 (extremely negative) 1 (not positive) to 5 (extremely positive) why does it use two scores? because research from psychology has revealed that we process positive and negative sentiment in parallel - hence mixed emotions. sentistrength can also report binary (positive/negative), trinary (positive/negative/neutral) and single scale (-4 to +4) results. sentistrength was originally developed for english and optimised for general short social web texts but can be configured for other languages and contexts by changing its input files - some variants are demonstrated below. quick tests (english version): enter text: output: dual, binary, trinary, scale keyword test : enter keywords (comma-separated list, no spaces): topic test : select domain (broad topic): films/movies mobile phones riots music politics hotels auto detect other languages : finnish, german, dutch spanish . russian, portuguese, french, arabic, polish, persian, swedish, greek, welsh, italian, turkish . download sentistrength sentistrength is free for academic research and is certified safe by softpedia . please contact the author for the commercial java version or a commercial license for the online version. the free version runs under windows only and is provided without liability or guarantees for any uses. downloading sentistrength and/or the configuration files signifies acceptance of these conditions. this version does not contain the keyword or domain classification facilities. register for the free sentistrength download - make sure to save the program and the data files (this does not do the binary/trinary/scale classifications). if sentistrength gives an error message when starting, please try downloading and installing the " microsoft .net framework redistributable package " and then try running sentistrength again. remember to use register new location in the file menu to point sentistrength to the location of the data files as soon as it loads, unless they are saved in the default location c:\sentstrength_data\. buy sentistrength a commercial licence for sentistrength is available for £1000 - please contact m.thelwall -at- wlv.ac.uk. the java version of sentistrength is normally used commercially. sentistrength is used by computing, language technology and market research companies in the us, europe and australia. some use the default english version and others have translated it into different languages or adopted it to integrate with their existing language technology systems. commercial users range from small start-ups to one of the world's top 10 largest corporations. java version the java version of sentistrength is similar to the windows version in core functions but has additional capabilities - see the sentistrength java manual (updated february 2017) and mac users' starting instructions (also helps in linux probably). it can conduct binary (positive/negative), trinary (positive/neutral/negative), single-scale classifications (-4 very negative to very positive +4) in addition to the standard type, and can conduct keyword-oriented and domain-oriented classifications. it also has a special mode for binary and trinary classification on longer texts. it allows wildcards in the idiom list file. to use the java version for research only (free), email from your academic email address. it can process about 16,000 tweets per second . for rjb users, here is some sample rjb code from adam pantanowitz , university of the witwatersrand. for python users, here is some sample python code from alec larsen, university of the witwatersrand. for python 3+ try this sample python code (or text version ) variant instead. unizip this jupyter notebook to use. for gate users, here is a gate wrapper to import sentistrength from mark greenwood and diana maynard , university of sheffield. instructions for using the gate plugin from alex ibollit stepanenko. for weka users, there is a sentistrength wrapper for the affectivetweets weka package by felipe bravo-marquez of waikato university that can be installed via the wekapackage manager . thank you to sooyeon jeong of mit for fixing sentistrength to work for android apps. about sentistrength sentistrength is a sentiment analysis (opinion mining) program. it is described and evaluated in the following peer-reviewed academic articles: thelwall, m., buckley, k., paltoglou, g. cai, d., & kappas, a. (2010). sentiment strength detection in short informal text . journal of the american society for information science and technology , 61(12), 2544–2558. thelwall, m., buckley, k., & paltoglou, g. (2012). sentiment strength detection for the social web , journal of the american society for information science and technology , 63(1), 163-173. thelwall, m., & buckley, k. (2013). topic-based sentiment analysis for the social web: the role of mood and issue-related words . journal of the american society for information science and technology , 64(8), 1608–1617. thelwall, m., & buckley, k., paltoglou, g., skowron, m., garcia, d., gobron, s., ahn, j., kappas, a., küster, d. & holyst, j.a. (2013). damping sentiment analysis in online communication: discussions, monologs and dialogs. in: a. gelbukh (ed.): cicling 2013, part ii, lncs 7817, pp. 1-12. springer, heidelberg. [turkish version] g. vural, b. b. cambazoglu, p. senkul, and o. tokgoz (2013) a framework for sentiment analysis in turkish: application to polarity detection of movie reviews in turkish , computer and information sciences iii, pp 437-445. thelwall, m. (2017). heart and soul: sentiment strength detection in the social web with sentistrength (summary book chapter). in: holyst, j. (ed.) cyberemotions: collective emotions in cyberspace. berlin, germany: springer (pp. 119-134). doi:10.1007/978-3-319-43639-5_7 [spanish version] vilares calvo, d., thelwall, m., & alonso, m.a. (2015). the megaphone of the people? spanish sentistrength for real-time analysis of political tweets . journal of information science . [ introduces an improved spanish sentiment strength detection version of sentistrength and shows spanish political tweets tend to amplify news stories. ] thelwall, m. (2018). gender bias in sentiment analysis . online information review , 42(1), 45-57. it has been applied in the following research projects, amongst others. thelwall, m., buckley, k., & paltoglou, g. (2011). sentiment in twitter events . journal of the american society for information science and technology, 62(2), 406-418. kucuktunc, o., cambazoglu, b.b., weber, i., & ferhatosmanoglu, h. (2012). a large-scale sentiment analysis for yahoo! answers , proceedings of the 5th acm international conference on web search and data mining .[used in yahoo!] weber, i, ukkonen, a., & gionis, a. (2012). answers, not links: extracting tips from yahoo! answers to address how-to web queries , proceedings of the fifth acm international conference on web search and data mining (wsdm '12). [used in yahoo!] pfitzner, r., garas, a., & schweitzer, f. (2012). emotional divergence influences information spreading in twitter , icwsm-12. garas, a., garcia, d., skowron, m., & schweitzer, f. (2012). emotional persistence in online chatting communities . scientific reports , 2, article 402. mihai grigore and christoph rosenkranz (2011). increasing the willingness to collaborate online: an analysis of sentiment-driven interactions in peer content production . icis 2011 proceedings. paper 20. g. vural, b. b. cambazog

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  REFERRER http://www.nominet.org.uk

  REGISTRAR Nominet UK

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  SERVER ac.uk.whois-servers.net

  ARGS ac.uk

  PORT 43

  TYPE domain

  REGISTERED no

DOMAIN

  NAME ac.uk

NSERVER

  NS0.JA.NET 193.63.94.20

  WS-FRA1.WIN-IP.DFN.DE 193.174.75.178

  NS1.SURFNET.NL 192.87.106.101

  NS2.JA.NET 193.63.105.17

  NS4.JA.NET 193.62.157.66

  NS3.JA.NET 193.63.106.103

  AUTH03.NS.UU.NET 198.6.1.83

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