Mobile Search Research Articles

Strategies of making and unmaking ethnic boundaries: Evidence on the Laz of Turkey

The main aim of this article is to explore different strategies of boundary making and unmaking by a minority ethnic group. I apply the theories of “boundary work” and constructivist understanding of ethnicity and nationhood to the case of the Laz, one of the autochthons of the Eastern Black Sea region of Turkey. I analyze two main strategies—boundary crossing and contraction—in the context of three sets of encounters and interactions, with Turks/Turkishness, people of Black Sea—Karadenizli—and Kurds/Kurdishness. First, I argue that assimilating into the official Turkish identity is one of the strategies adopted by the ethnic Laz. The Laz are incorporated into Turkishness both by their search for economic mobility, status, and by assimilationist policies of the state especially aimed at the spread of Turkish. To become a full-fledged true member of the nation and access to potential benefits, Turkishness through language shift has been realized that allowed boundary crossing of the Laz. Second, I state that despite the efforts of the top-down assimilationist policies, noncontentious ethnic identities can be reproduced by means of symbolic boundaries. The Laz contextually activate symbolic boundaries in informal settings by contracting from other people of Black Sea—Karadenizli—or ethnic Turkishness. The ethnic language is substituted by nonthreatening ethnic performances and rhetoric, less marked and more subjective traits of self-asserted differences. Such symbolic boundaries correspond to unofficial forms of hierarchies and competition over local belongings. Third, the analysis of the Laz–Kurd relationship unveils that ethnic boundaries can be redefined according to changing conditions. The impact of the Kurds on the Laz identity, either by means of personal acquaintances or the relationship between the state and the Kurdish national movement, is imperative. It triggers contradictions in the Laz identity by revealing new potential redefinitions and recasting of boundaries.

Effects of investor attention on commodity futures markets

China has recently seen surging retail investor participation in commodity futures markets and rapid adoption of mobile Internet interface. We study two questions with these developments using search frequency from Baidu, the leading Chinese Internet search engine, as a measure of retail investor attention. First we examine whether the relation between retail investor attention and stock returns exists for futures markets where short-selling constraint faced by retail investors is relaxed. Second, we investigate whether mobile Internet searches serve as an effective attention measure as traditional PC-based Internet searches. We find that higher attention predicts larger positive and negative returns in the futures markets, consistent with the argument of short-selling constraint in stock market. We also find that the predictive power of search frequency is mainly from PC-based searches and not from mobile searches.

Making in-store payment enjoyable by adopting mobile payment

The increasing penetration rate of smartphones changes behaviors based on mobile unique features. Our research provides a first attempt to better understand the adoption of in-store smartphone usage to enhance a brick-and-mortar experience. More particularly, it focuses on proximity mobile payment (p-m-payment), which corresponds to a recent tendency of shoppers to finalize the transaction through their smartphone while they shop in a store. Using a perceived value approach, this paper identifies utilitarian, hedonic and social benefits as well as financial and privacy risks as key drivers of adoption for p-m-payment.A comparison between the drivers of this new in-store mobile usage and the ones for more familiar tasks such as mobile information search, highlights clear differences in what drives intention, as shoppers are more experienced with the latter.The paper discusses the implications for mobile and channel researches and provides suggestions for retailers to facilitate and take advantage of p-m-payment.

Estimating local commuting patterns from geolocated Twitter data

The emergence of large stores of transactional data generated by increasing use of digital devices presents a huge opportunity for policymakers to improve their knowledge of the local environment and thus make more informed and better decisions. A research frontier is hence emerging which involves exploring the type of measures that can be drawn from data stores such as mobile phone logs, Internet searches and contributions to social media platforms and the extent to which these measures are accurate reflections of the wider population. This paper contributes to this research frontier, by exploring the extent to which local commuting patterns can be estimated from data drawn from Twitter. It makes three contributions in particular. First, it shows that heuristics applied to geolocated Twitter data offer a good proxy for local commuting patterns; one which outperforms the current best method for estimating these patterns (the radiation model). This finding is of particular significance because we make use of relatively coarse geolocation data (at the city level) and use simple heuristics based on frequency counts. Second, it investigates sources of error in the proxy measure, showing that the model performs better on short trips with higher volumes of commuters; it also looks at demographic biases but finds that, surprisingly, measurements are not significantly affected by the fact that the demographic makeup of Twitter users differs significantly from the population as a whole. Finally, it looks at potential ways of going beyond simple frequency heuristics by incorporating temporal information into models.

UMCR

Although mobile application ecosystems have experienced tremendous growth in recent years, retrieving content of mobile applications that serves a key to mobile content search engines still faces grand challenges. Compared to web content retrieval, it is much more difficult to capture content in mobile applications due to the diversity of applications and the lack of Uniform Resource Locator indices. In this study, we propose and implement a <underline>u</underline>ser interaction-driven <underline>m</underline>obile <underline>c</underline>ontent <underline>r</underline>etrieval (UMCR) system to address such issues, which is the first mobile content crawler in the current literature. UMCR is a distributed system that contains many measurement nodes, each of which combines the user interaction path traversing (UIPT) and Deep Package Inspection (DPI) together to obtain mobile content. UIPT determines the events of user interactions in various applications to capture the static content such as text and images, in which a traversal depth termination scheme and an optional cut-off component are adopted to balance the content coverage and traversing efficiency. Meanwhile, the analysis based on DPI is responsible for extracting the videos as well as digging the infrastructural information and performance metrics. In addition, a distributed traversal scheduling method is designed for UIPT tasks to improve the throughput and scalability in large-scale content retrieval. Experiments on retrieving content of 64 real mobile applications demonstrate that UMCR can handle diverse mobile applications efficiently. The scheduler can improve throughput by 3 times compared to the legacy arbitrary task assignment strategy.

How Users Search the Mobile Web: A Model for Understanding the Impact of Motivation and Context on Search Behaviors

Abstract Purpose This study explores how search motivation and context influence mobile Web search behaviors. Design/methodology/approach We studied 30 experienced mobile Web users via questionnaires, semi-structured interviews, and an online diary tool that participants used to record their daily search activities. SQLite Developer was used to extract data from the users’ phone logs for correlation analysis in Statistical Product and Service Solutions (SPSS). Findings One quarter of mobile search sessions were driven by two or more search motivations. It was especially difficult to distinguish curiosity from time killing in particular user reporting. Multi-dimensional contexts and motivations influenced mobile search behaviors, and among the context dimensions, gender, place, activities they engaged in while searching, task importance, portal, and interpersonal relations (whether accompanied or alone when searching) correlated with each other. Research limitations The sample was comprised entirely of college students, so our findings may not generalize to other populations. More participants and longer experimental duration will improve the accuracy and objectivity of the research. Practical implications Motivation analysis and search context recognition can help mobile service providers design applications and services for particular mobile contexts and usages. Originality/value Most current research focuses on specific contexts, such as studies on place, or other contextual influences on mobile search, and lacks a systematic analysis of mobile search context. Based on analysis of the impact of mobile search motivations and search context on search behaviors, we built a multi-dimensional model of mobile search behaviors.

Search, Mining, and Their Applications on Mobile Devices

In recent years, mobile devices have become the most popular interface for users to retrieve and access information: recent reports show that users spend significantly more time and issue more search queries on mobile devices than on desktops in the United States. 1 The accelerated growth of mobile usage brings unique opportunities to the information retrieval and data mining research communities. Mobile devices capture rich contextual and personal signals that can be leveraged to accurately predict users’ intent for serving more relevant content and can even proactively provide novel zero-query recommendations. Apple Siri, Google Now, and Microsoft Cortana are recent examples of such emerging systems. Furthermore, mobile devices constantly generate a huge amount of sensor footprints (e.g., GPS, motion sensors) and user activity data (e.g., used apps) that are often missing from their desktop counterparts. These new sources of implicit and explicit user feedback are valuable for discovering actionable knowledge, and designing better systems that serve each individual the right content at the right time and location. In addition, by aggregating mobile interactions across individuals, one can infer interesting conclusions beyond search and recommendation. Generating real-time traffic estimates is one example of such applications. This special issue focuses on research problems of search, mining, and their applications in mobile devices. Topics of interest in this special issue include but are not limited to mobile data mining and management, mobile search, personalization and recommendation, mobile user interfaces and human-computer interaction, and new applications in the mobile environment. The aim of this special issue is to bring together top experts across multiple disciplines, including information retrieval, data mining, mobile computing, and cyberphysical systems, such that academic and industrial researchers can exchange ideas and share the latest developments on the state of the art and practice of mobile search and mobile data mining.

Channels for search and purchase: Does mobile Internet matter?

Recent industry reports indicate that consumers own four digital devices on an average, and switching devices during shopping is the “new normal.” The addition of mobile Internet as a new channel of search and purchase has spurred the adoption of the digital medium, and easy accessibility of the Internet on multiple devices is influencing shopping patterns. A consumer may prefer some channels for search and others for purchase or use a combination of channels to search and purchase simultaneously. As a new channel, it is unclear 1) whether mobile Internet offers greater search or purchase benefits and 2) what type of products are more suitable for mobile Internet search and purchase. In this study, we develop a framework that describes the factors that drive the use of mobile Internet in a multi-channel environment. We test the framework using survey data from a sample of U.S consumers. The main findings from our study indicate that 1) the choice of channel combinations that include mobile relative to other channel combinations increases with an increase in perceived search convenience of mobile channel. 2) in the digital channel, mobile and desktop differ in their utility along search dimensions. The probability of choosing channel combinations that include mobile increases due to search convenience whereas desktop is attractive due to perceived gains of price comparison search; and 3) mobile Internet search increases for consumers searching for utilitarian products. The insights from this study deepen our understanding of how digital media is used in the search-purchase process and have important managerial implications.

The transition from traditional banking to mobile internet finance: an organizational innovation perspective - a comparative study of Citibank and ICBC

The development of Financial Technology (FinTech) in areas such as mobile Internet, cloud computing, big data, search engines, and blockchain technology have significantly changed the financial industry. FinTech is expected to overturn the traditional banking business model, forcing banks to upgrade and transform.This study adopts a comparative case study method to contrast and analyze the Industrial and Commercial Bank of China (ICBC) and Citibank. It analyzes the strategies, organizations, HR systems, and product innovations adopted by these two banks in response to the impact of FinTech. This paper proposes an “electric vehicle” mode for ICBC and an “airplane mode” for Citibank. Further, it describes the difficulties encountered by the Chinese banking industry and proposes some feasible ways to upgrade. “Technology power” will become the core competitive concept for the financial institutions of the future.

Mathematical Model for Information Technology Infusion for Healthcare Sector in Nigeria

In this article, an IT infusion model was developed for the Nigerian health sector using teaching hospitals in Nigeria. The different IT technologies used by medical practitioners were identified. Structured questionnaires were used to elicit knowledge from respondents selected from teaching hospitals located in Nigeria. The results showed that the nurses and doctors with less than 5 years working experience were common users of IT. The results for the IT infusion showed that the earliest IT component in the health sector was the personal computer since the year 1994 followed by mobile phone and search engines by the year 1996 with the projector infused by the year 2001. The infusion model for the total number of users for each IT component was formulated using polynomial functions of degree, n with respect to t – the number of years after the base year of infusion of IT device. The IT infusion model developed in this paper can be used to forecast the future growth of IT within the healthcare sectors.

Applying push-pull-mooring to investigate channel switching behaviors: M-shopping self-efficacy and switching costs as moderators

Abstract The push-pull-mooring model was applied in this study to investigate consumer channel switching intention related to physical and mobile stores. Push effects include mobile information search behavior (with the perceived benefit and cost of search as antecedents) and perceived value (with perceived service quality and perceived price as antecedents) of products and services obtained at a physical store. Pull effects were consumers’ evaluations of the mobile store attractiveness (with mobile characteristics and perceived quality of mobile store as antecedents). Additionally, mobile shopping self-efficacy and switching cost were hypothesized as the mooring effects that intervene in the push and pull effects. A total of 403 valid questionnaires were collected from Taiwanese m-shopping consumers, and structural equation modeling was adopted for quantitative analysis and hypotheses testing. The results indicated that push and pull effects have direct impacts on switching intention, with the exception of the perceived cost of the search. Mooring effects, including m-shopping self-efficacy, procedural and relational switch costs, have a varying degree of moderating effect on the information search behavior, perceived value, mobile store attractiveness and switch intention. This study concluded that retailers should pay more attention to raising consumer value on both physical and mobile channels to diversify their businesses. This not only offers more channel options for consumers to come into contact with retailers (cross-channel retention), but also prevents consumer cross-channel free-riding behavior, and ultimately reduce switching to other retailers.

Human segmentation of infrared image for mobile robot search

In the search robotics field, human target segmentation method plays a basic preprocessing step in the visual guidance. However, with the wide application of the infrared sensor on robot vision, traditional segmentation methods are facing more challenges of low-contrast, overlapping and blurring targets, and complex background. This paper introduces an infrared human segmentation approach that integrates the improved pulse coupled neural network (PCNN), the curvature gravity gradient tensor (CGGT) and the mathematical morphology to address these above problems. This approach starts with an improved PCNN segmentation model. Local dynamic synapse weights are designed to enhance the synchronous pulsing ability of the improved PCNN model with similar inputs, and a reformed threshold is conducted to guide the process of segmentation. Moreover, eigenvalues of CGGT are guaranteed in this model as linking coefficients, in order to capture the edges and details of human target more exactly in segmentation. Lastly, the segmentation result is repaired by morphology operators, to ensure the integrity of the target region and the independent noise removal. Experiments on 200 real infrared images captured by the mobile robot CQSearcher I, demonstrate that our method is superior over the other classic segmentation methods in both the subjective visual performance and the objective indicators of misclassification error and f-measure.

Housing tenure, mobility and labour market behaviour

This study investigated the relationships between housing, housing markets and the labour market. It considered factors such as geographic mobility, reservation wages (i.e. the minimum wage that an unemployed individual can accept) and job search behaviours across a range of housing tenures.

Legal Issues: Google, Success and the European Union

With 110 million hits (in 0.16 seconds), Google is a popular news topic in all respects. The big stories of the day are the launch of Google’s new wireless service–described in one report as “game-changing”–and the an update to its mobile search algorithms that will prioritize mobile-friendly websites in presenting results to searches conducted on mobile devices–described by a couple of commentators as “mobilegeddon” and “phonepocolypse” Superlatives and hyperbolic comments seem to accompany stories about Google. With a market capitalization of over $300 billion (sometimes approaching $400 billion), Google is one of the most highly valued companies in the world, ahead of long-time firms such as General Electric, Wal-Mart and Boeing, and battling neck-and-neck with Berkshire-Hathaway and Microsoft. All of this from a company that began in a garage office barely 16 years ago. Growth like that doesn’t come without rubbing a few people the wrong way and Google has run into more than its share of public relations and legal challenges over the years. The latest such legal challenge was next on the list of news topics on my search, charges that Google’s search results and its Android mobile operating system violate the European Union’s antitrust laws.

Considerations for the Mobile Web. Paradigm Shift

IntroductionI n recent years, the number of devices (smartphones, phablets, tablets) and of device users has grown considerably, impacting on user behavior, especially with respect to Web browsing habits.To support this trend, Google has undertaken and still undertakes numerous efforts, by continuously updating its search algorithm in order to meet the users' needs effectively. On the other hand, according to Google's latest algorithms, website owners constantly struggle to optimize content in order to score higher in search results [1]. On the whole, these optimization efforts benefit both the indexing process and users.One of the reasons why Google offers priority to mobile-optimized web pages and favors the mobile approach is that nowadays most users use their devices to search online [2]. Mobile online searches have been growing yearly, with 2015 registering mobile-based than desktop-based online searches [3].Google states that more Google searches take place on devices than on computers in 10 countries including the US and Japan, however, without giving further details [4]. This fact, which seems to confirm Google's interest in Web, has stimulated greater efforts toward offering users better experience [5].As depicted in Figure 1 timeline, Google made public its interest in browsing as early as 2010, and the first major step was taken in October 2014, when the company introduced the Mobile Usability report in Webmaster Tools [6].Of the many steps taken by Google in this direction [6], we would like to mention two which, in our opinion, have the strongest impact on Web:* Mobile-friendly algorithm update - Mobilegeddon (April 21, 2015);* Mobile-first index (November 2016).2Mobile-Friendly Algorithm UpdateOn 21 April 2015, Google launched the Mobile-friendly algorithm update (MFAU), their new ranking system (nicknamed Mobilegeddon), through which search engine results pages (SERPs) are influenced by the website's mobile friendliness [7]. This update of the search algorithms only impacts mobile-based online searches, regardless of the language used or of the country of origin [8].MFAU aims to significantly alter search results on devices by giving priority to mobile-friendly instead of non-mobilefriendly websites. This change does not affect desktop/laptop-based searches. Google's intention is to facilitate access to mobilefriendly websites for device users [1]. A mobile-friendly website is essentially a normal website which works well and is displayed properly on both desktop/laptop and devices. The site can be shrunk down so as to be small enough to be displayed on a device. Even if the user must zoom and scroll, the website is displayed and works properly. The experience may not be perfect, but the website can be decently displayed and browsed [9].Due to MFAU, the websites whose owners failed to implement a strategy to adapt the sites themselves as well as their content to device experience will rank lower than mobile-friendly websites [8].In order to give website owners time to prepare for imminent changes and to give the world the chance to benefit from their advantages, Google made public its intention to introduce MFAU two months before it was due to be launched [10].Following this statement, Google noticed a 4,7% growth in the number of mobile-friendly websites in March and April 2015. Fear of MFAU (hence the apocalyptic connotations of the label Mobilegeddon) and of potential traffic loss made many website owners upgrade them to mobile-friendly level [11].A lot of people were persuaded that the April 2015 upgrade would have a devastating effect on businesses lacking presence online [12], but this proved less serious than expected. Those monitoring ranking changes did not notice anything that would justify Google's statements according to which this update surpassed previous Panda or Penguin updates [13]. …

Attitudes toward mobile search ads: a study among Mexican millennials

PurposeThe purpose of this study is to conduct a survey of Mexican millennials to measure the extent of negative bias and perceived advertising value they experienced toward the ads they encountered while performing a search for local products and services from their smartphones.Design/methodology/approachUsing a paper survey with a scenario question, responses were collected from 1,215 millennial smartphone owners about the strategies they used for scanning mobile search organic and sponsored results and quickly reaching the information they needed when performing a mobile search. The 315 participants who reported clicking on ads were further surveyed on their perceptions of ad informativeness, entertainment, irritation and credibility. These constructs were used as the predictors of advertising value in a structural equations model which was estimated with partial least squares.FindingsA substantial bias against sponsored results was found, with two-thirds of respondents skipping the ads when performing a mobile search from their smartphones. However, 28.2 per cent reported clicking on the most relevant result without regard to it being organic or sponsored, and an additional 5.6 per cent reported clicking on an ad as their first strategy. In the structural model, all four hypothesized antecedents of advertising value were significant, and some gender differences were detected.Practical implicationsWith the increasing penetration of smartphones, and rapid growth of mobile search, these results are particularly relevant for local merchants, who can use mobile search ads to leverage their location and communicate with searching consumers at the precise moment when they are most receptive to timely and relevant advertising.Originality/valueThis study is the first to measure the extent of consumer bias against sponsored results in a mobile search, and the first empirical estimation of the advertising value of mobile-sponsored results.

Personalized Mobile Searching Approach Based on Combining Content-Based Filtering and Collaborative Filtering

Resources in cloud computing platforms such as Amazon, Google AppEngine, and Microsoft Azure are a natural fit to remedy the lack of local resources in mobile devices, which creates a new space of mobile search to improve the availability of cloud resources. In essence, mobile search is a context-aware and personalized activity since mobile devices' inherent movability allows people to retrieve information anytime and anywhere. However, current mobile search products are always far from personalized and are accuracy centered on the convergence of mobile platforms. In this paper, a hybrid filtering mechanism is proposed to eliminate irrelevant or less relevant results for personalized mobile search, which combines content-based filtering and collaborative filtering. The former filters the results according to the mobile user's feature model generated from the user's query history, and the latter filters the results using the user's social network, which is constructed from the user's communication history. Experiments show that the filtering mechanism can significantly improve the user's personalized and precise searching experience on mobile phones.

The Effects of Visualization and Synchronization on Clustered-Based Mobile Web Search

ABSTRACTDespite the increasing use of mobile web in our everyday lives, mobile web search remains a challenging task mainly due to the intensive scrolling inherent in linear presentation of search engine results (SERs) on the small screen of a mobile device. Drawing on the cognitive load theory and information foraging theory, this study aims to improve user performance in mobile web search by proposing two new artifacts—radial visualization of SERs clusters and synchronization of clusters and individual SERs presentations. These artifacts are hypothesized to improve search efficiency and/or navigation efficiency without affecting search effectiveness. This study also examines a possible moderating effect of search task type (open-ended vs. close-ended tasks). We implemented four mobile web search systems that reflect four combinations of different visualization and synchronization settings and empirically evaluated them using a controlled experiment. The results show that the radial visualization improves search efficiency and navigation efficiency, particularly for the open-ended tasks. In addition, synchronous presentation improves navigation efficiency in terms of path similarity.

Histone degradation in response to DNA damage enhances chromatin dynamics and recombination rates.

Nucleosomes are essential for proper chromatin organization and the maintenance of genome integrity. Histones are post-translationally modified and often evicted at sites of DNA breaks, facilitating the recruitment of repair factors. Whether such chromatin changes are localized or genome-wide is debated. Here we show that cellular levels of histones drop 20-40% in response to DNA damage. This histone loss occurs from chromatin, is proteasome-mediated and requires both the DNA damage checkpoint and the INO80 nucleosome remodeler. We confirmed reductions in histone levels by stable isotope labeling of amino acids in cell culture (SILAC)-based mass spectrometry, genome-wide nucleosome mapping and fluorescence microscopy. Chromatin decompaction and increased fiber flexibility accompanied histone degradation, both in response to DNA damage and after artificial reduction of histone levels. As a result, recombination rates and DNA-repair focus turnover were enhanced. Thus, we propose that a generalized reduction in nucleosome occupancy is an integral part of the DNA damage response in yeast that provides mechanisms for enhanced chromatin mobility and homology search.

Dehashing: Server-Side Context-Aware Feature Reconstruction for Mobile Visual Search

Due to the prevalence of mobile devices, mobile search becomes a more convenient way than desktop search. Different from the traditional desktop search, mobile visual search needs more consideration for the limited resources on mobile devices (e.g., bandwidth, computing power, and memory consumption). The state-of-the-art approaches show that the bag-of-words (BoW) model is robust for image and video retrieval; however, the large vocabulary tree might not be able to be loaded on the mobile device. We observe that recent works mainly focus on designing compact feature representations on mobile devices for bandwidth-limited network (e.g., 3G) and directly adopt feature matching on remote servers (cloud). However, the compact (binary) representation might fail to retrieve target objects (images and videos). Based on the hashed binary codes, we propose a dehashing process that reconstructs BoW by leveraging the computing power of remote servers. To mitigate the information loss from binary codes, we further utilize contextual information (e.g., GPS) to reconstruct a context-aware BoW for better retrieval results. Experiment results show that the proposed method can achieve competitive retrieval accuracy as BoW while only transmitting few bits from mobile devices.