Searching for Product Experience Attributes in Online Information Sources

Using the Web, consumers not only find product characteristics from manufacturers and sellers; they can also exchange opinions with other third parties. Learning about such “experience attributes” builds confidence in purchasing decisions and establishes trust between parties in transactions. However, little is known about the search process for these experience attributes. In the current study, 65 participants researched a product, reporting its characteristics as well as salient experience attributes. By analyzing their search diaries and questionnaire responses, patterns for finding product characteristics versus experience attributes were compared. Precision on task was the same, however, product characteristics searches were likely to originate at search engines. Seller-dominated sites were favored over independent sites in searches for product characteristics, while the opposite was true for experience attributes. Finally, searches for experience attributes were not as broad or deep as those for product characteristics, suggesting that consumers focus their attention on fewer sources

Learning the Lingo? Gender, Prestige and Linguistic Adaptation in Review Communities

Women and men communicate differently in both face-to- face and computer-mediated environments. We study linguistic patterns considered gendered in reviews contributed to the Internet Movie Database. IMDb has been described as a male-majority community, in which females contribute fewer reviews and enjoy less prestige than males. Analyzing reviews posted by prolific males and females, we hypothesize that females adjust their communication styles to be in sync with their male counterparts. We find evidence that while certain characteristics of “female language” persevere over time (e.g., frequent use of pronouns) others (e.g., hedging) decrease with time. Surprisingly, we also find that males often increase their use of “female” features. Our results indicate, that even when they resemble men’s reviews linguistically, women’s reviews still enjoy less prestige and smaller audiences

Profile Interview with Faculty Mentor Dr. Jason Ware

Dr. Jason Ware is a clinical assistant professor in the Honors College with a courtesy appointment in the College of Education

What's Congress Doing on Twitter?

As Twitter becomes a more common means for officials to communicate with their constituents, it becomes more important that we understand how officials use these communication tools. Using data from 380 members of Congress’ Twitter activity during the winter of 2012, we find that officials frequently use Twitter to advertise their political positions and to provide information but rarely to request political action from their constituents or to recognize the good work of others. We highlight a number of differences in communication frequency between men and women, Senators and Representatives, Republicans and Democrats. We provide groundwork for future research examining the behavior of public officials online and testing the predictive power of officials’ social media behavior

Tweeting Vertically? Elected Officials’ Interactions with Citizens on Twitter

Enthusiasts propose that social media promotes vertical political communication, giving citizens the opportunity to interact directly with their representatives. However, skeptics claim that politicians avoid direct engagement with constituents, using technology to present a façade of interactivity instead. This study explores if and how elected officials in three regions of the world are using Twitter to interact with the public. We examine the Twitter activity of 15 officials over a period of six months. We show that in addition to the structural features of Twitter that are designed to promote interaction, officials rely on language to foster or to avoid engagement. It also provides yet more evidence that the existence of interactive features does not guarantee interactivity

Headlines data for social media popularity prediction

This dataset is part of a larger project on using headlines to predict the social media popularity of news articles. The dataset consists of two headlines corpora -- The Guardian and New York Times -- collected in 2014 using news outlet APIs. Each corpus includes a unique headline identifier (to enable recreating the corpus by querying the relevant API), the extracted features (news values, style, metadata), and the corresponding popularity on Twitter and Facebook

Chicago Politicians on Twitter

This paper uses data from 1,042 tweets posted by or mentioning Chicago Aldermen or Mayor Rahm Emanuel to examine how Chicago politicians use social media. Twitter provides a public communication medium in which constituents and their representatives can have two-way conversations that others can witness and record, and we used qualitative and social network methods to examine conversations between Chicagoans and representatives in city government. We coded the contents of each tweet over the two-week time period (e.g., official business, fundraising) and created representations of the social networks created by the users’ following behaviors. These networks indicate who receives politicians’ tweets and help identify the audiences for political messaging in social media. Our analysis indicates that Chicago’s Aldermen and Mayor use Twitter for social conversations more often than political ones, and that only a small number of Aldermen dominate the resulting conversation networks.Sponsorship: Social Network Research Group at IIT, IIT Graduate Colleg

Interferometric modification of the Lockheed Martin PSTAR system to facilitate three dimensional airspace surveillance

Thesis (M.S.) University of Alaska Fairbanks, 2011The Lockheed Martin PSTAR is a monostatic radar system that provides range, azimuth, and radial velocity information of detected targets. While this system is useful for airspace surveillance in remote locations due to its portability and durability, it lacks the ability to record target information and the ability to estimate target elevation angle, resulting in a vertical arc of possible target locations. Due to a desire to use the PSTAR for applications that require logging three-dimensional target information, a spatial interferometric modification has been implemented. The PSTAR estimates range from pulse propagation delay and azimuth angle from the orientation of the antenna on a rotating pedestal. Two PSTAR antennas were removed from their housings and mounted, vertically separated, in a custom enclosure allowing for the estimation of elevation angle through spatial interferometry. The reflected signal is received by both antennas, mixed to baseband, and then the two pairs of I/Q channels are simultaneously sampled at 1 MS/s. Target elevation angle is estimated by determining the phase difference of the target's reflection received by the two vertically spaced antennas. Range, azimuth, and radial velocity are also estimated. All data collection was implemented in LabVIEW and data post-processing was implemented in MATLAB.1. Introduction -- 1.1. Unmanned aerial vehicles -- 1.2. FAA requirements -- 1.3. PFRR requirements -- 1.4. Thesis overview -- 2. Description of PSTAR -- 2.1. PSTAR hardware -- 2.2. PSTAR testing -- 2.3. Internal PSTAR communications -- 2.4. Beam pattern -- 3. Estimation of target parameters -- 3.1. Radar fundamentals -- 3.1.1. Power -- 3.1.1.1. Radar equation -- 3.1.1.2. Noise -- 3.1.1.3. Signal to noise ratio -- 3.1.2. Azimuth -- 3.1.3. Range -- 3.1.3.1. Range ambiguity -- 3.1.4. Doppler velocity -- 3.1.4.1. Doppler velocity ambiguity -- 3.2. 3D Target location -- 3.2.1. Triangulation -- 3.2.2. Interferometry -- 3.2.2.1. Elevation ambiguity -- 4. Data collection -- 4.1. Azimuth data -- 4.1.1. Digital data from pedestal -- 4.1.2. Resolver -- 4.1.3. Hall effect sensor -- 4.2. I/Q data -- 4.2.1. Analog to digital converter -- 4.2.2. Dual antenna -- 4.2.3. PXI system -- 4.3. Modified PSTAR system -- 4.4. Data collection program -- 4.4.1. North alignment -- 4.4.2. I/Q data -- 4.4.2.1. Calibration data -- 4.4.2.2. Operational data -- 5. Data processing -- 5.1. Overview -- 5.2. Calibration -- 5.3. Signal conditioning -- 5.3.1. Data packaging -- 5.3.2. Removal of voltage discontinuities -- 5.4. Target detection -- 5.4.1. Azimuth -- 5.4.2. Range -- 5.4.2.1. Matched filter -- 5.4.2.2. Moving target indicator -- 5.4.2.3. Oversampled point target detection filter -- 5.4.3. Doppler velocity -- 5.4.4. Elevation angle -- 5.5. Processing demand -- 6. Testing and verification -- 6.1. Simulated data -- 6.2. Cooperative target tests -- 7. Conclusions and future improvements -- 7.1. Unused algorithms -- 7.1.1. Detailed calibration -- 7.1.2. Cluttermap -- 7.2. North alignment -- 7.3. FPGA based data collection -- 7.4. Replace PSTAR components -- Bibliography -- Appendix