TipTop Technologies

Last updated
TipTop Technologies
TipTop logo.jpg
Type of site
Search engine
Available in English
FoundedFrank D’Amico
Key peopleFrank D’Amico founder / [CEO]
URL FeelTipTop.com
LaunchedJune 2009
Current statusOnline, Beta

TipTop Technologies is a real-time web and social search engine with a platform for semantic analysis of natural language. Tip-Top Search provides results capturing individual and group sentiment, opinions, and experiences there from the content of various sorts such as real-time messages from Twitter or consumer product reviews on Amazon.com. [1] TipTop Technologies and ITC Infotech have worked together to develop a search interface for both enterprise and consumer applications. [2] Tip-Top's products are part of the "emerging Web 3.0 applications which use semantic technologies to augment the underlying Web system's functionalities." [3]

Jonathan AlBright professor at Elon University, found videos generated by TipTop Technologies software on YouTube in his research into artificial intelligence, described it as AI-generated "fake news". [4]

Through semantic analysis of large data sets, TipTop gleaned behavioral insights from Tweets around events like Halloween, [5] Thanksgiving, [6] Holiday Gifting, [7] the Super Bowl, [8] and the Academy Awards: 2010 Oscar Nominees coverage. [9] Sentiment analysis, concept trend tracking, and real-time market research are other applications included in the TipTop Search product. [10] TipTop's insight engine solves the problem of real-time data noise, and its ability to "sort the 'good tweets' from the 'bad tweets' when it comes to a product, service, or a region..." [11]

In addition, products like TipTop Shopping with customizable search widgets bring together consumer reviews, social search, and sentiment analysis enabling product comparisons across attributes like the overall value and aiding purchasing decisions through user-driven product tips and pits. [12] TipTop Finance adds another complexity to real-time search results by incorporating corporate sentiment, company stock tickers, and social media into TipTop's existing social search platform. [13] Additional success applying semantic technologies has been with polling, "if you compare these Gallup [14] results with TipTop, a sentiment engine based on Twitter, the results are not way off. It does surprise you but it tells me that sentiment analysis in case of public opinion about a burning social issue or a famous personality is relatively easier.". [15] With the increasing amount of unstructured, opinion-oriented, and user-generated content available on the Web, TipTop's technology aims to make sense of all this data, and deliver it in a useful way for consumer and enterprise users alike. [16]

TipTop Technologies is a privately held company with its headquarters in Silicon Valley, California, and team members located globally.

Related Research Articles

Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." Written resources may include websites, books, emails, reviews, and articles. High-quality information is typically obtained by devising patterns and trends by means such as statistical pattern learning. According to Hotho et al. (2005) we can distinguish between three different perspectives of text mining: information extraction, data mining, and a knowledge discovery in databases (KDD) process. Text mining usually involves the process of structuring the input text, deriving patterns within the structured data, and finally evaluation and interpretation of the output. 'High quality' in text mining usually refers to some combination of relevance, novelty, and interest. Typical text mining tasks include text categorization, text clustering, concept/entity extraction, production of granular taxonomies, sentiment analysis, document summarization, and entity relation modeling.

Sentiment analysis is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social media, and healthcare materials for applications that range from marketing to customer service to clinical medicine. With the rise of deep language models, such as RoBERTa, also more difficult data domains can be analyzed, e.g., news texts where authors typically express their opinion/sentiment less explicitly.

BasisTech is a software company specializing in applying artificial intelligence techniques to understanding documents and unstructured data written in different languages. It has headquarters in Somerville, Massachusetts and offices in San Francisco, Washington, D.C., London, Tel Aviv, and Tokyo. Its legal name is Basis Technology Corp.

Social media measurement, also called social media controlling, is the management practice of evaluating successful social media communications of brands, companies, or other organizations.

Amit Sheth is a computer scientist at University of South Carolina in Columbia, South Carolina. He is the founding Director of the Artificial Intelligence Institute, and a Professor of Computer Science and Engineering. From 2007 to June 2019, he was the Lexis Nexis Ohio Eminent Scholar, director of the Ohio Center of Excellence in Knowledge-enabled Computing, and a Professor of Computer Science at Wright State University. Sheth's work has been cited by over 48,800 publications. He has an h-index of 106, which puts him among the top 100 computer scientists with the highest h-index. Prior to founding the Kno.e.sis Center, he served as the director of the Large Scale Distributed Information Systems Lab at the University of Georgia in Athens, Georgia.

Marketing buzz or simply buzz—a term used in viral marketing—is the interaction of consumers and users of a product or service which amplifies or alters the original marketing message. This emotion, energy, excitement, or anticipation about a product or service can be positive or negative. Buzz can be generated by intentional marketing activities by the brand owner or it can be the result of an independent event that enters public awareness through social or traditional media such as newspapers. Marketing buzz originally referred to oral communication but in the age of Web 2.0, social media such as Facebook, Twitter, Instagram and YouTube are now the dominant communication channels for marketing buzz.

Search-based applications are software applications in which a search engine platform is used as the core infrastructure for information access and reporting. Search-based applications use semantic technologies to aggregate, normalize and classify unstructured, semi-structured and/or structured content across multiple repositories, and employ natural language technologies for accessing the aggregated information.

Yebol was a vertical "decision" search engine that had developed a knowledge-based, semantic search platform. Based in San Jose, California, Yebol's artificial intelligence human intelligence-infused algorithms automatically cluster and categorize search results, web sites, pages and contents that it presents in a visually indexed format that is more aligned with initial human intent. Yebol used association, ranking and clustering algorithms to analyze related keywords or web pages. Yebol presented as one of its goals the creation of a unique "homepage look" for every possible search term.

The Ubiquitous Knowledge Processing Lab is a research lab at the Department of Computer Science at the Technische Universität Darmstadt. It was founded in 2006 by Iryna Gurevych.

The social data revolution is the shift in human communication patterns towards increased personal information sharing and its related implications, made possible by the rise of social networks in the early 2000s. This phenomenon has resulted in the accumulation of unprecedented amounts of public data.

idio Ltd. is an enterprise software company that produces and implements products for brands and publishers. To do so, idio uses its cloud-hosted platform, which incorporates modules for large-scale content aggregation and structuring, content analytics, multi-channel marketing automation, and customer insight generation. idio has offices in London and Exeter in the UK.

The fields of marketing and artificial intelligence converge in systems which assist in areas such as market forecasting, and automation of processes and decision making, along with increased efficiency of tasks which would usually be performed by humans. The science behind these systems can be explained through neural networks and expert systems, computer programs that process input and provide valuable output for marketers.

<span class="mw-page-title-main">Viralheat</span> Subscription-based software service

Viralheat was a subscription-based software service for social media management that helps clients monitor and analyze consumer-created content. It was first released in beta in May 2009. Viralheat raised $75,000 in seed capital in December 2009 and $4.25 million of venture capital from the Mayfield Fund in 2011.

<span class="mw-page-title-main">Topsy Labs</span> U.S. social search and analytics company

Topsy Labs was a social search and analytics company based in San Francisco, California. The company was a certified Twitter partner and maintained a comprehensive index of tweets, numbering in the hundreds of billions, dating back to Twitter's inception in 2006.

NetOwl is a suite of multilingual text and identity analytics products that analyze big data in the form of text data – reports, web, social media, etc. – as well as structured entity data about people, organizations, places, and things.

Social media mining is the process of obtaining big data from user-generated content on social media sites and mobile apps in order to extract actionable patterns, form conclusions about users, and act upon the information, often for the purpose of advertising to users or conducting research. The term is an analogy to the resource extraction process of mining for rare minerals. Resource extraction mining requires mining companies to shift through vast quantities of raw ore to find the precious minerals; likewise, social media mining requires human data analysts and automated software programs to shift through massive amounts of raw social media data in order to discern patterns and trends relating to social media usage, online behaviours, sharing of content, connections between individuals, online buying behaviour, and more. These patterns and trends are of interest to companies, governments and not-for-profit organizations, as these organizations can use these patterns and trends to design their strategies or introduce new programs, new products, processes or services.

Semantic queries allow for queries and analytics of associative and contextual nature. Semantic queries enable the retrieval of both explicitly and implicitly derived information based on syntactic, semantic and structural information contained in data. They are designed to deliver precise results or to answer more fuzzy and wide open questions through pattern matching and digital reasoning.

<span class="mw-page-title-main">Social media analytics</span> Process of gathering and analyzing data from social media networks

Social media analytics is the process of gathering and analyzing data from social networks such as Facebook, Instagram, LinkedIn, or Twitter. A part of social media analytics is called social media monitoring or social listening. It is commonly used by marketers to track online conversations about products and companies. One author defined it as "the art and science of extracting valuable hidden insights from vast amounts of semi-structured and unstructured social media data to enable informed and insightful decision making."

Luminoso is a Cambridge, MA-based text analytics and artificial intelligence company. It spun out of the MIT Media Lab and its crowd-sourced Open Mind Common Sense (OMCS) project.


  1. TipTop Search FAQs
  2. Press Trust of India, "TipTop and ITC Infotech launch innovative search engine" Business Standard, November 16, 2009
  3. "Web 3.0: The Dawn of Semantic Search" IEEE Computer, James Hendler. January 2010.
  4. Albright, Jonathan (2017-01-19). "📺FakeTube: AI-Generated News on YouTube". Medium. Retrieved 2023-03-28.
  5. KLIV Radio, The Economy & Silicon Valley Report with TipTop CEO, Shyam Kapur November 4, 2009
  6. "Happy Linksgiving" Vertical Measures. November 25, 2009
  7. "TipTop reveals the best and most popular gifts of 2009" AltSearchEngines. December 20, 2009
  8. TipTop Technologies, 2010 Super Bowl XLIV Commercials: TipTop's SB44 Ad Ratings February 10, 2010
  9. TipTop Technologies, Watching the 2010 Academy Awards & Walking the Red Carpet Via TipTop Social Search & Sentiment, March 9, 2010
  10. Gardner, Author Gail. "How to Use TipTop for Real Time Market Research". GrowMap. Retrieved 2023-03-28.{{cite web}}: |first= has generic name (help)
  11. "Gathering Twitter Intelligence With TipTop" inteligia, Ian Smith. February 22, 2010
  12. "TipTop Technologies Launches Revolutionary Comparison Shopping Site" NewDesignWorld. December 18, 2009
  13. "Corporate Sentiment, Company Stock Tickers & Social Media Converge in TipTop Finance" TipTop Technologies Press Release. May 14, 2010.
  14. Inc, Gallup. "Gallup Daily: Obama Job Approval". Gallup.com. Retrieved 2023-03-28.{{cite web}}: |last= has generic name (help)
  15. Mohan, Priyank (2010-04-28). "Priyank Mohan: Sentiment Analysis: Can you get it right by just automating it?". Priyank Mohan. Retrieved 2023-03-28.
  16. J. MURALI, "Opinion gathering: making sense of unstructured data" The Hindu. January 4, 2010.