Text, Web, and Social Analytics

Text, Web, and Social Analytics 1) Text analytics is the subset of text mining that handles information retrieval and extraction, plus data mining. Answer: FALSE 2) Categorization and clustering of documents during text mining differ only in the preselection of categories. Answer: TRUE 3) Articles and auxiliary verbs are assigned little value in text mining and are usually filtered out. Answer: TRUE 4) In the patent analysis case study, text mining of thousands of patents held by the firm and its competitors helped improve competitive intelligence, but was of little use in identifying complementary products. Answer: FALSE 5) Regional accents present challenges for natural language processing. Answer: TRUE 6) In the Hong Kong government case study, reporting time was the main benefit of using SAS Business Analytics to generate reports. Answer: TRUE 7) In the financial services firm case study, text analysis for associate-customer interactions were completely automated and could detect whether they met the company's standards. Answer: TRUE 8) In text mining, if an association between two concepts has 7% support, it means that 7% of the documents had both concepts represented in the same document. Answer: TRUE 9) In sentiment analysis, sentiment suggests a transient, temporary opinion reflective of one's feelings. Answer: FALSE 10) Current use of sentiment analysis in voice of the customer applications allows companies to change their products or services in real time in response to customer sentiment. Answer: TRUE 11) In sentiment analysis, it is hard to classify some subjects such as news as good or bad, but easier to classify others, e.g., movie reviews, in the same way. Answer: TRUE 12) Generally, making a search engine more efficient makes it less effective. Answer: TRUE 13) Search engine optimization (SEO) techniques play a minor role in a Web site's search ranking because only well-written content matters. Answer: FALSE 14) Clickstream analysis does not need users to enter their perceptions of the Web site or other feedback directly to be useful in determining their preferences. Answer: TRUE 15) Since little can be done about visitor Web site abandonment rates, organizations have to focus their efforts on increasing the number of new visitors. Answer: FALSE 16) Decentralization, the need for specialized skills, and immediacy of output are all attributes of Web publishing when compared to industrial publishing. Answer: FALSE 17) Consistent high quality, higher publishing frequency, and longer time lag are all attributes of industrial publishing when compared to Web publishing. Answer: FALSE 18) Web site visitors who critique and create content are more engaged than those who join networks and spectate. Answer: TRUE 19) Descriptive analytics for social media feature such items as your followers as well as the content in online conversations that help you to identify themes and sentiments. Answer: FALSE 20) Companies understand that when their product goes "viral," the content of the online conversations about their product does not matter, only the volume of conversations. Answer: FALSE 21) In the opening vignette, the architectural system that supported Watson used all the following elements EXCEPT A) massive parallelism to enable simultaneous consideration of multiple hypotheses. B) an underlying confidence subsystem that ranks and integrates answers. C) a core engine that could operate seamlessly in another domain without changes. D) integration of shallow and deep knowledge. Answer: C 22) In text mining, tokenizing is the process of A) categorizing a block of text in a sentence. B) reducing multiple words to their base or root. C) transforming the term-by-document matrix to a manageable size. D) creating new branches or stems of recorded paragraphs. Answer: A 23) All of the following are challenges associated with natural language processing EXCEPT A) dividing up a text into individual words in English. B) understanding the context in which something is said. C) distinguishing between words that have more than one meaning. D) recognizing typographical or grammatical errors in texts. Answer: A 24) What data discovery process, whereby objects are categorized into predetermined groups, is used in text mining? A) clustering B) association C) classification D) trend analysis Answer: C 25) In the research literature case study, the researchers analyzing academic papers extracted information from which source? A) the paper abstract B) the paper keywords C) the main body of the paper D) the paper references Answer: A 26) In sentiment analysis, which of the following is an implicit opinion? A) The hotel we stayed in was terrible. B) The customer service I got for my TV was laughable. C) The cruise we went on last summer was a disaster. D) Our new mayor is great for the city. Answer: B 27) In the Whirlpool case study, the company sought to better understand information coming from which source? A) customer transaction data B) delivery information C) customer e-mails D) goods moving through the internal supply chain Answer: C 28) What do voice of the market (VOM) applications of sentiment analysis do? A) They examine customer sentiment at the aggregate level. B) They examine employee sentiment in the organization. C) They examine the stock market for trends. D) They examine the "market of ideas" in politics. Answer: A 29) How is objectivity handled in sentiment analysis? A) It is ignored because it does not appear in customer sentiment. B) It is incorporated as a type of sentiment. C) It is clarified with the customer who expressed it. D) It is identified and removed as facts are not sentiment. Answer: D 30) In text analysis, what is a lexicon? A) a catalog of words, their synonyms, and their meanings B) a catalog of customers, their words, and phrase C) a catalog of letters, words, phrases and sentences D) a catalog of customers, products, words, and phrase Answer: A 31) What types of documents are BEST suited to semantic labeling and aggregation to determine sentiment orientation? A) medium- to large-sized documents B) small- to medium-sized documents C) large-sized documents D) collections of documents Answer: B 32) What does Web content mining involve? A) analyzing the universal resource locator in Web pages B) analyzing the unstructured content of Web pages C) analyzing the pattern of visits to a Web site D) analyzing the PageRank and other metadata of a Web page Answer: B 33) Breaking up a Web page into its components to identify worthy words/terms and indexing them using a set of rules is called A) preprocessing the documents. B) document analysis. C) creating the term-by-document matrix. D) parsing the documents. Answer: D 34) Search engine optimization (SEO) is a means by which A) Web site developers can negotiate better deals for paid ads. B) Web site developers can increase Web site search rankings. C) Web site developers index their Web sites for search engines. D) Web site developers optimize the artistic features of their Web sites. Answer: B 35) What are the two main types of Web analytics? A) old-school and new-school Web analytics B) Bing and Google Web analytics C) off-site and on-site Web analytics D) data-based and subjective Web analytics Answer: C 36) Web site usability may be rated poor if A) the average number of page views on your Web site is large. B) the time spent on your Web site is long. C) Web site visitors download few of your offered PDFs and videos. D) users fail to click on all pages equally. Answer: C 37) Understanding which keywords your users enter to reach your Web site through a search engine can help you understand A) the hardware your Web site is running on. B) the type of Web browser being used by your Web site visitors. C) most of your Web site visitors' wants and needs. D) how well visitors understand your products. Answer: D 38) Which of the following statements about Web site conversion statistics is FALSE? A) Web site visitors can be classed as either new or returning. B) Visitors who begin a purchase on most Web sites must complete it. C) The conversion rate is the number of people who take action divided by the number of visitors. D) Analyzing exit rates can tell you why visitors left your Web site. Answer: B 39) What is one major way in which Web-based social media differs from traditional publishing media? A) Most Web-based media are operated by the government and large firms. B) They use different languages of publication. C) They have different costs to own and operate. D) Web-based media have a narrower range of quality. Answer: C 40) What does advanced analytics for social media do? A) It helps identify your followers. B) It identifies links between groups. C) It examines the content of online conversations. D) It identifies the biggest sources of influence online. Answer: C 41) IBM's Watson utilizes a massively parallel, text mining—focused, probabilistic evidencebased computational architecture called ________. Answer: DeepQA 42) ________, also called homonyms, are syntactically identical words with different meanings. Answer: Polysemes 43) When a word has more than one meaning, selecting the meaning that makes the most sense can only be accomplished by taking into account the context within which the word is used. This concept is known as ________. Answer: word sense disambiguation 44) ________ is a technique used to detect favorable and unfavorable opinions toward specific products and services using large numbers of textual data sources. Answer: Sentiment analysis 45) In the Mining for Lies case study, a text based deception-detection method used by Fuller and others in 2008 was based on a process known as ________, which relies on elements of data and text mining techniques. Answer: message feature mining 46) At a very high level, the text mining process can be broken down into three consecutive tasks, the first of which is to establish the ________. Answer: Corpus 47) Because the term-document matrix is often very large and rather sparse, an important optimization step is to reduce the ________ of the matrix. Answer: dimensionality 48) ________ is mostly driven by sentiment analysis and is a key element of customer experience management initiatives, where the goal is to create an intimate relationship with the customer. Answer: Voice of the customer (VOC) 49) When viewed as a binary feature, ________ classification is the binary classification task of labeling an opinionated document as expressing either an overall positive or an overall negative opinion. Answer: polarity 50) Web pages contain both unstructured information and ________, which are connections to other Web pages. Answer: hyperlinks 51) Web ________ are used to automatically read through the contents of Web sites. Answer: crawlers/spiders 52) A(n) ________ is one or more Web pages that provide a collection of links to authoritative Web pages. Answer: hub 53) A(n) ________ engine is a software program that searches for Web sites or files based on keywords. Answer: search 54) In the Lotte.com retail case, the company deployed SAS for Customer Experience Analytics to better understand the quality of customer traffic on their Web site, classify order rates, and see which ________ had the most visitors. Answer: channels 55) ________ Web analytics refers to measurement and analysis of data relating to your company that takes place outside your Web site. Answer: Off-site 56) A ________ Web site contains links that send traffic directly to your Web site. Answer: referral 57) ________ statistics help you understand whether your specific marketing objective for a Web page is being achieved. Answer: Conversion 58) In the Social Network Analysis (SNA) for Telecommunications case, SNA can be used to detect ________, i.e., those visitors who about to leave the website and persuade them to stay with you. Answer: churners 59) ________ is a connections metric for social networks that measures the ties that actors in a network have with others that are geographically close. Answer: Propinquity 60) ________ is a segmentation metric for social networks that measures the strength of the bonds between actors in a social network. Answer: Cohesion 61) How would you describe information extraction in text mining? Answer: Information extraction is the identification of key phrases and relationships within text by looking for predefined objects and sequences in text by way of pattern matching. 62) Natural language processing (NLP), a subfield of artificial intelligence and computational linguistics, is an important component of text mining. What is the definition of NLP? Answer: NLP is a discipline that studies the problem of "understanding" the natural human language, with the view of converting depictions of human language into more formal representations in the form of numeric and symbolic data that are easier for computer programs to manipulate. 63) In the security domain, one of the largest and most prominent text mining applications is the highly classified ECHELON surveillance system. What is ECHELON assumed to be capable of doing? Answer: Identifying the content of telephone calls, faxes, e-mails, and other types of data and intercepting information sent via satellites, public switched telephone networks, and microwave links 64) Describe the query-specific clustering method as it relates to clustering. Answer: This method employs a hierarchical clustering approach where the most relevant documents to the posed query appear in small tight clusters that are nested in larger clusters containing less similar documents, creating a spectrum of relevance levels among the documents. 65) Identify, with a brief description, each of the four steps in the sentiment analysis process. Answer: 1. Sentiment Detection: Here the goal is to differentiate between a fact and an opinion, which may be viewed as classification of text as objective or subjective. 2. N-P Polarity Classification: Given an opinionated piece of text, the goal is to classify the opinion as falling under one of two opposing sentiment polarities, or locate its position on the continuum between these two polarities. 3. Target Identification: The goal of this step is to accurately identify the target of the expressed sentiment. 4. Collection and Aggregation: In this step all text data points in the document are aggregated and converted to a single sentiment measure for the whole document. 66) In what ways does the Web pose great challenges for effective and efficient knowledge discovery through data mining? Answer: ∙ The Web is too big for effective data mining. The Web is so large and growing so rapidly that it is difficult to even quantify its size. Because of the sheer size of the Web, it is not feasible to set up a data warehouse to replicate, store, and integrate all of the data on the Web, making data collection and integration a challenge. ∙ The Web is too complex. The complexity of a Web page is far greater than a page in a traditional text document collection. Web pages lack a unified structure. They contain far more authoring style and content variation than any set of books, articles, or other traditional text-based document. ∙ The Web is too dynamic. The Web is a highly dynamic information source. Not only does the Web grow rapidly, but its content is constantly being updated. Blogs, news stories, stock market results, weather reports, sports scores, prices, company advertisements, and numerous other types of information are updated regularly on the Web. ∙ The Web is not specific to a domain. The Web serves a broad diversity of communities and connects billions of workstations. Web users have very different backgrounds, interests, and usage purposes. Most users may not have good knowledge of the structure of the information network and may not be aware of the heavy cost of a particular search that they perform. ∙ The Web has everything. Only a small portion of the information on the Web is truly relevant or useful to someone (or some task). Finding the portion of the Web that is truly relevant to a person and the task being performed is a prominent issue in Web-related research. 67) What is search engine optimization (SEO) and why is it important for organizations that own Web sites? Answer: Search engine optimization (SEO) is the intentional activity of affecting the visibility of an e-commerce site or a Web site in a search engine's natural (unpaid or organic) search results. In general, the higher ranked on the search results page, and more frequently a site appears in the search results list, the more visitors it will receive from the search engine's users. Being indexed by search engines like Google, Bing, and Yahoo! is not good enough for businesses. Getting ranked on the most wide used search engines and getting ranked higher than your competitors are what make the difference. 68) What is the difference between white hat and black hat SEO activities? Answer: An SEO technique is considered white hat if it conforms to the search engines' guidelines and involves no deception. Because search engine guidelines are not written as a series of rules or commandments, this is an important distinction to note. White-hat SEO is not just about following guidelines, but about ensuring that the content a search engine indexes and subsequently ranks is the same content a user will see. Black-hat SEO attempts to improve rankings in ways that are disapproved by the search engines, or involve deception or trying to trick search engine algorithms from their intended purpose. 69) Why are the users' page views and time spent on your Web site important metrics? Answer: If people come to your Web site and don't view many pages, that is undesirable and your Web site may have issues with its design or structure. Another explanation for low page views is a disconnect in the marketing messages that brought them to the site and the content that is actually available. Generally, the longer a person spends on your Web site, the better it is. That could mean they're carefully reviewing your content, utilizing interactive components you have available, and building toward an informed decision to buy, respond, or take the next step you've provided. On the contrary, the time on site also needs to be examined against the number of pages viewed to make sure the visitor isn't spending his or her time trying to locate content that should be more readily accessible. 70) What are the three categories of social media analytics technologies and what do they do? Answer: ∙ Descriptive analytics: Uses simple statistics to identify activity characteristics and trends, such as how many followers you have, how many reviews were generated on Facebook, and which channels are being used most often. ∙ Social network analysis: Follows the links between friends, fans, and followers to identify connections of influence as well as the biggest sources of influence. ∙ Advanced analytics: Includes predictive analytics and text analytics that examine the content in online conversations to identify themes, sentiments, and connections that would not be revealed by casual surveillance.