Business Intelligence, 3e (Sharda/Delen/Turban)
Chapter 5 Text, Web, and Social Analytics
1) Text analytics is the subset of text mining that handles information retrieval and extraction,
plus data mining.
2) Categorization and clustering of documents during text mining differ only in the preselection
of categories.
3) Articles and auxiliary verbs are assigned little value in text mining and are usually filtered out.
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.
5) Regional accents present challenges for natural language processing.
6) In the Hong Kong government case study, reporting time was the main benefit of using SAS
Business Analytics to generate reports.
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.
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.
9) In sentiment analysis, sentiment suggests a transient, temporary opinion reflective of one’s
feelings.
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.
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.
12) Generally, making a search engine more efficient makes it less effective.
13) Search engine optimization (SEO) techniques play a minor role in a Web site’s search
ranking because only well-written content matters.
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.
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.
16) Decentralization, the need for specialized skills, and immediacy of output are all attributes of
Web publishing when compared to industrial publishing.
17) Consistent high quality, higher publishing frequency, and longer time lag are all attributes of
industrial publishing when compared to Web publishing.
18) Web site visitors who critique and create content are more engaged than those who join
networks and spectate.
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.
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.
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.
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.
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.
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
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
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.
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
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.
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.
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
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
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
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.
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.
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
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.
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.
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.
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.
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.
41) IBM’s Watson utilizes a massively parallel, text mining—focused, probabilistic evidence-
based computational architecture called ________.
42) ________, also called homonyms, are syntactically identical words with different meanings.
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 ________.
44) ________ is a technique used to detect favorable and unfavorable opinions toward specific
products and services using large numbers of textual data sources.
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.
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 ________.
47) Because the term-document matrix is often very large and rather sparse, an important
optimization step is to reduce the ________ of the matrix.
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.
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.
50) Web pages contain both unstructured information and ________, which are connections to
other Web pages.
51) Web ________ are used to automatically read through the contents of Web sites.
52) A(n) ________ is one or more Web pages that provide a collection of links to authoritative
Web pages.
53) A(n) ________ engine is a software program that searches for Web sites or files based on
keywords.
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.
55) ________ Web analytics refers to measurement and analysis of data relating to your
company that takes place outside your Web site.
56) A ________ Web site contains links that send traffic directly to your Web site.
57) ________ statistics help you understand whether your specific marketing objective for a
Web page is being achieved.
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.
59) ________ is a connections metric for social networks that measures the ties that actors in a
network have with others that are geographically close.
60) ________ is a segmentation metric for social networks that measures the strength of the
bonds between actors in a social network.
61) How would you describe information extraction in text mining?
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?
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?
64) Describe the query-specific clustering method as it relates to clustering.
65) Identify, with a brief description, each of the four steps in the sentiment analysis process.
66) In what ways does the Web pose great challenges for effective and efficient knowledge
discovery through data mining?
67) What is search engine optimization (SEO) and why is it important for organizations that own
Web sites?
68) What is the difference between white hat and black hat SEO activities?
69) Why are the users’ page views and time spent on your Web site important metrics?
70) What are the three categories of social media analytics technologies and what do they do?