Customer References as Marketing Practice in Company Web sites - Content and Discourse Analysis

Työn tarkoituksena oli tutkia sisältö- ja diskurssianalyysin avulla kuinka yritykset viestivät asiakasreferenssejä verkkosivuillaan. Työssä keskityttiin tutkimaan yritysten referenssikuvausten teemoja ja diskursseja, sekä sitä kuinka referenssisuhde rakentuu diskursiivisesti referenssikuvauksissa. Tutkimukseen valittiin kolme suomalaista ICT-alan yritystä: Nokia, TietoEnator ja F-Secure. Aineisto koostuu 140:stä yritysten WWW-sivuilta kerätystä referenssikuvauksesta. Sisältöanalyysin tuloksena havaittiin, että referenssikuvaukset keskittyvät kuvaamaan yksittäisiä tuote- tai projektitoimituksia referenssiasiakkaille kyseisten asiakassuhteiden valossa. Analyysin tuloksena tunnistettiin kolme diskurssia: hyötydiskurssi, sitoutumisen diskurssi sekä teknologisen eksperttiyden diskurssi. Diskurssit paljastavat referenssikuvausten retoriset keinot ja konstruoivat referenssisuhteen ja toimittajan subjektiposition eri näkökulmista. Pääpaino referenssikuvauksissa on toimittajan ratkaisun tuomissa hyödyissä. Diskurssit tuottavat referenssisuhteesta kuvan hyötyjä tuovana ja läheisenä asiakassuhteena, joka tarjoaa väylän ulkopuolisiin kyvykkyyksiin ja teknologioihin. Toimittaja esitetään referenssikuvauksissa diskurssista riippuen hyötyjen tuojana, luotettavana partnerina sekä kokeneena eksperttinä. Referenssiasiakas sen sijaan esitetään vain yhdestä näkökulmasta stereotyyppisesti tärkeänä ja tyytyväisenä asiakkaana.

Web Content Customization

Tavoitteena on tutkia sisällön räätälöintiä Internetissä. Yritysten tarjoama sisällön määrä WWW-sivuillaan on kasvanut räjähdysmäisesti. Räätälöinnin avulla asiakkaat saavat juuri haluamaansa ja tarvitsemaansa sisältöä. Räätälöinti edellyttää asiakkaiden profilointia. Asiakastietojen kerääminen aiheuttaa huolta yksityisyyden menettämisestä. Tutkimus toteutetaan case-tutkimuksena. Tutkimuksen kohteena on viisi yritystä, jotka toimivat sisällön tarjoajina. Tutkimus pohjautuu valmiiseen aineistoon sekä osallistuvaan havainnointiin kohde yrityksistä. Sisällön räätälöinnistä voidaan havaita neljä eri perus lähestymistapaa. Profilointi toteutetaan pääsääntöisesti joko asiakkaan itse antamien tietojen pohjalta tai havainnoimalla hänen käyttäytymistään WWW-sivulla. Tulevaisuudessa tarvitaan selkeät pelisäännöt asiakastietojen keräämiseen ja käyttämiseen. Asiakkaat haluavat räätälöityä sisältöä, mutta sisällön tarjoajien on saavutettava heidän luottamuksensa yksityisyyden suojasta. Luottamuksen merkitys kasvaa entisestään, kun räätälöintiä kehitetään pidemmälle.

Search Interfaces on the Web: Querying and Characterizing

Current-day web search engines (e.g., Google) do not crawl and index a significant portion of theWeb and, hence, web users relying on search engines only are unable to discover and access a large amount of information from the non-indexable part of the Web. Specifically, dynamic pages generated based on parameters provided by a user via web search forms (or search interfaces) are not indexed by search engines and cannot be found in searchers’ results. Such search interfaces provide web users with an online access to myriads of databases on the Web. In order to obtain some information from a web database of interest, a user issues his/her query by specifying query terms in a search form and receives the query results, a set of dynamic pages that embed required information from a database. At the same time, issuing a query via an arbitrary search interface is an extremely complex task for any kind of automatic agents including web crawlers, which, at least up to the present day, do not even attempt to pass through web forms on a large scale. In this thesis, our primary and key object of study is a huge portion of the Web (hereafter referred as the deep Web) hidden behind web search interfaces. We concentrate on three classes of problems around the deep Web: characterization of deep Web, finding and classifying deep web resources, and querying web databases. Characterizing deep Web: Though the term deep Web was coined in 2000, which is sufficiently long ago for any web-related concept/technology, we still do not know many important characteristics of the deep Web. Another matter of concern is that surveys of the deep Web existing so far are predominantly based on study of deep web sites in English. One can then expect that findings from these surveys may be biased, especially owing to a steady increase in non-English web content. In this way, surveying of national segments of the deep Web is of interest not only to national communities but to the whole web community as well. In this thesis, we propose two new methods for estimating the main parameters of deep Web. We use the suggested methods to estimate the scale of one specific national segment of the Web and report our findings. We also build and make publicly available a dataset describing more than 200 web databases from the national segment of the Web. Finding deep web resources: The deep Web has been growing at a very fast pace. It has been estimated that there are hundred thousands of deep web sites. Due to the huge volume of information in the deep Web, there has been a significant interest to approaches that allow users and computer applications to leverage this information. Most approaches assumed that search interfaces to web databases of interest are already discovered and known to query systems. However, such assumptions do not hold true mostly because of the large scale of the deep Web – indeed, for any given domain of interest there are too many web databases with relevant content. Thus, the ability to locate search interfaces to web databases becomes a key requirement for any application accessing the deep Web. In this thesis, we describe the architecture of the I-Crawler, a system for finding and classifying search interfaces. Specifically, the I-Crawler is intentionally designed to be used in deepWeb characterization studies and for constructing directories of deep web resources. Unlike almost all other approaches to the deep Web existing so far, the I-Crawler is able to recognize and analyze JavaScript-rich and non-HTML searchable forms. Querying web databases: Retrieving information by filling out web search forms is a typical task for a web user. This is all the more so as interfaces of conventional search engines are also web forms. At present, a user needs to manually provide input values to search interfaces and then extract required data from the pages with results. The manual filling out forms is not feasible and cumbersome in cases of complex queries but such kind of queries are essential for many web searches especially in the area of e-commerce. In this way, the automation of querying and retrieving data behind search interfaces is desirable and essential for such tasks as building domain-independent deep web crawlers and automated web agents, searching for domain-specific information (vertical search engines), and for extraction and integration of information from various deep web resources. We present a data model for representing search interfaces and discuss techniques for extracting field labels, client-side scripts and structured data from HTML pages. We also describe a representation of result pages and discuss how to extract and store results of form queries. Besides, we present a user-friendly and expressive form query language that allows one to retrieve information behind search interfaces and extract useful data from the result pages based on specified conditions. We implement a prototype system for querying web databases and describe its architecture and components design.

Designing and Implementing Mouse Emulation to Touchscreen Operated Mobile Web Browsers

Browsing the web has become one of the most important features in high end mobile phones and in the future more and more people will be using mobile phone for web browsing. Large touchscreens improve browsing experience but many web sites are designed to be used with a mouse. A touchscreen differs substantially from a mouse as a pointing device and therefore mouse emulation logic is required in the browsers to make more web sites usable. This Master's thesis lists the most significant cases where the differences of a mouse and a touchscreen affect web browsing. Five touchscreen mobile phones and their web browsers were evaluated to find out if and how these cases are handled in them. Also as a part of this thesis, a simple QtWebKit based mobile web browser with advanced mouse emulation model was implemented, aiming to solve all the problematic cases. The conclusion of this work is that it is feasible to emulate a mouse with a touchscreen and thus deliver good user experience in mobile web browsing. However, current highend touchscreen mobile phones have relatively underdeveloped mouse emulations in their web browsers and there is a lot to improve.