Contextual effects in speed perception may occur at an early stage of processing

How does nearby motion affect the perceived speed of a target region? When a central drifting Gabor patch is surrounded by translating noise, its speed can be misperceived over a fourfold range. Typically, when a surround moves in the same direction, perceived centre speed is reduced; for opposite-direction surrounds it increases. Measuring this illusion for a variety of surround properties reveals that the motion context effects are a saturating function of surround speed (Experiment I) and contrast (Experiment II). Our analyses indicate that the effects are consistent with a subtractive process, rather than with speed being averaged over area. In Experiment III we exploit known properties of the motion system to ask where these surround effects impact. Using 2D plaid stimuli, we find that surround-induced shifts in perceived speed of one plaid component produce substantial shifts in perceived plaid direction. This indicates that surrounds exert their influence early in processing, before pattern motion direction is computed. These findings relate to ongoing investigations of surround suppression for direction discrimination, and are consistent with single-cell findings of direction-tuned suppressive and facilitatory interactions in primary visual cortex (V1).

Contextual modulation involves suppression and facilitation from the center and the surround

In psychophysics, cross-orientation suppression (XOS) and cross-orientation facilitation (XOF) have been measured by investigating mask configuration on the detection threshold of a centrally placed patch of sine-wave grating. Much of the evidence for XOS and XOF comes from studies using low and high spatial frequencies, respectively, where the interactions are thought to arise from within (XOS) and outside (XOF) the footprint of the classical receptive field. We address the relation between these processes here by measuring the effects of various sizes of superimposed and annular cross-oriented masks on detection thresholds at two spatial scales (1 and 7 c/deg) and on contrast increment thresholds at 7 c/deg. A functional model of our results indicates the following (1) XOS and XOF both occur for superimposed and annular masks. (2) XOS declines with spatial frequency but XOF does not. (3) The spatial extent of the interactions does not scale with spatial frequency, meaning that surround-effects are seen primarily at high spatial frequencies. (4) There are two distinct processes involved in XOS: direct divisive suppression and modulation of self-suppression. (5) Whether XOS or XOF wins out depends upon their relative weights and mask contrast. These results prompt enquiry into the effect of spatial frequency at the single-cell level and place new constraints on image-processing models of early visual processing. © ARVO.

The contextual evaluation of research on sexually explicit materials

This thesis criticises many psychological experiments on 'pornography' which attempt to demonstrate how 'pornography' causes and/or equals rape. It challenges simplistic definitions of 'pornography', arguing that sexually explicit materials (SEM) are constructed and interpreted in a number of different ways; and demonstrates that how, when and where materials are depicted or viewed will influence perceptions and reactions. In addition, it opposes the overreliance on male undergraduates as participants in 'porn' research. Theories of feminist psychology and reflexivity are used throughout the thesis, and provide a detailed contextual framework in a complex area. Results from a number of interlinking studies which use a variety of methodological approaches (focus groups, questionnaires and content analysis), indicate how contextual issues are omitted in much existing research on SEM. These include the views and experiences participants' hold prior to completing SEM studies; their opinions about those who 'use' 'pornography'; their understanding of key terms linked with SEM (eg: pornography and erotica); and discussions of sexual magazines aimed at male and female audiences. Participants' reactions to images and texts associated with SEM presented in different contexts are discussed. Three main conclusions are drawn from this thesis. Firstly, images deemed 'pornographic' differ through historical and cultural periods' and political, economic and social climates, so 'experimental' approaches may not always be the most appropriate research tool. Secondly, there is not one definition, source, or factor which may be named 'pornography'; and thirdly the context and presentation of materials influence how images are perceived and reacted to. The thesis argues a number of factors influence view of 'pornography', suggesting SEM may be 'in the eye of the beholder'.

Classification and contextual enhancement of remotely sensed data

The aims of the project were twofold: 1) To investigate classification procedures for remotely sensed digital data, in order to develop modifications to existing algorithms and propose novel classification procedures; and 2) To investigate and develop algorithms for contextual enhancement of classified imagery in order to increase classification accuracy. The following classifiers were examined: box, decision tree, minimum distance, maximum likelihood. In addition to these the following algorithms were developed during the course of the research: deviant distance, look up table and an automated decision tree classifier using expert systems technology. Clustering techniques for unsupervised classification were also investigated. Contextual enhancements investigated were: mode filters, small area replacement and Wharton's CONAN algorithm. Additionally methods for noise and edge based declassification and contextual reclassification, non-probabilitic relaxation and relaxation based on Markov chain theory were developed. The advantages of per-field classifiers and Geographical Information Systems were investigated. The conclusions presented suggest suitable combinations of classifier and contextual enhancement, given user accuracy requirements and time constraints. These were then tested for validity using a different data set. A brief examination of the utility of the recommended contextual algorithms for reducing the effects of data noise was also carried out.

Lithological mapping of Northwest Argentina with remote sensing data using tonal, textural and contextual features

Tonal, textural and contextual properties are used in manual photointerpretation of remotely sensed data. This study has used these three attributes to produce a lithological map of semi arid northwest Argentina by semi automatic computer classification procedures of remotely sensed data. Three different types of satellite data were investigated, these were LANDSAT MSS, TM and SIR-A imagery. Supervised classification procedures using tonal features only produced poor classification results. LANDSAT MSS produced classification accuracies in the range of 40 to 60%, while accuracies of 50 to 70% were achieved using LANDSAT TM data. The addition of SIR-A data produced increases in the classification accuracy. The increased classification accuracy of TM over the MSS is because of the better discrimination of geological materials afforded by the middle infra red bands of the TM sensor. The maximum likelihood classifier consistently produced classification accuracies 10 to 15% higher than either the minimum distance to means or decision tree classifier, this improved accuracy was obtained at the cost of greatly increased processing time. A new type of classifier the spectral shape classifier, which is computationally as fast as a minimum distance to means classifier is described. However, the results for this classifier were disappointing, being lower in most cases than the minimum distance or decision tree procedures. The classification results using only tonal features were felt to be unacceptably poor, therefore textural attributes were investigated. Texture is an important attribute used by photogeologists to discriminate lithology. In the case of TM data, texture measures were found to increase the classification accuracy by up to 15%. However, in the case of the LANDSAT MSS data the use of texture measures did not provide any significant increase in the accuracy of classification. For TM data, it was found that second order texture, especially the SGLDM based measures, produced highest classification accuracy. Contextual post processing was found to increase classification accuracy and improve the visual appearance of classified output by removing isolated misclassified pixels which tend to clutter classified images. Simple contextual features, such as mode filters were found to out perform more complex features such as gravitational filter or minimal area replacement methods. Generally the larger the size of the filter, the greater the increase in the accuracy. Production rules were used to build a knowledge based system which used tonal and textural features to identify sedimentary lithologies in each of the two test sites. The knowledge based system was able to identify six out of ten lithologies correctly.

Disentangling individual and contextual shopping motivations

Shopping motivations have been extensively studied in marketing literature. However, what research names motivations may represent two different constructs: depending on studies, they are defined either individual permanent characteristics depending on consumer personality (motivational trait), or temporary states of mind depending on consumption contexts (motivational states). The objective of this paper is to stress the difference between these two types of motivations and to disentangle their effects on consumer behavior.

Disentangle contextual and permanent individual motivations:an application to shopping behavior

Past studies resulted in conflicting definitions of consumer motivation. On the one hand, motivations are seen as the consumer’s characteristics that shape her general behavior (motivational trait). On the other hand, they are seen as contextual variables representing the reason why the individual is behaving specific to today’s context (motivational state). The objective of this research is to stress the difference between these two concepts and to understand the impact of each on consumer behavior. We applied our empirical study to shopping motivations; our results show a strong interaction between motivational trait and motivational state. Problem and Hypothesis On the one hand, Westbrook and Black (1985) consider shopping motivations as individual permanent characteristics. This concept is shared by other researchers (Rohm and Swaminathan 2004), which show that some shoppers are functional (they shop for convenience, information seeking, and time saving) while some others are hedonic (they shop for social interaction, bargain hunting and browsing). On the other hand, Kaltcheva and Weitz (2006) define motivations as a contextual orientation changing over time, depending on the situation, and show that contextual shopping motivations have a strong impact on shopping behavior. From our knowledge, no research specifically examined the respective impact of both these shopping motivation types. To deal with this issue, we used the notions of “traits” and “states” that have been largely used in marketing research to designate respectively a permanent characteristic of the individual and a temporary orientation of the consumer (Mowen 2000). The reversal theory (Apter 2001) suggests that two opposite states exist: the telic and the paratelic states. In the telic state, individuals set goals for themselves, must be disciplined to reach these goals, and do not behave in accordance with their personal trait. In the paratelic state, individuals are seeking arousal and enjoyment, do not set rules, and one could postulate that they act in accordance with their natural tendencies. Based on these considerations, we hypothesize the following process: in situations involving paratelic states, hedonic as well as functional individuals should behave according to their natural traits, whereas in situations involving telic states, hedonic people should inhibit their natural propensity to enjoy shopping and behave similarly to functional people. Hence, we postulate the following: Hypothesis: Compared to shoppers with functional motivational trait, shoppers with hedonic motivational trait will a) significantly display more hedonic shopping behavior intentions in a condition of paratelic motivational state, and b) not display more hedonic shopping behavior intentions in a condition a telic motivational state Empirical Research First, 108 participants were asked to fill a multi-items scale about their shopping habits, which actually measured their shopping motivational traits. This questionnaire allowed us to highlight four different dimensions in shopping motivational traits: social interaction, novelty/utility seeking, bargain hunting, and browsing. According to their scores on different items, participants were classified as functional or as hedonic on each of these four dimensions (a single individual may be hedonic on some dimensions and functional on others). Then, participants were then induced to adopt either a telic or a paratelic shopping motivational state while reading an appropriate scenario. Finally, participants were asked for their shopping behavior intentions in response to the shopping context. Four items were developed, corresponding to the four shopping motivational trait dimensions we found with our factor analysis. Results As we found four dimensions in shopping motivational trait, we set up four quasi-experimental designs to capture the entire phenomenon: for each dimension, a 2 (motivational trait) x 2 (motivational state) design was built, where the dependant variable was the shopping behavior element corresponding to the studied dimension. Four 2 x 2 Anovas were performed to assess the interaction between motivational trait and motivational state. Concerning the three dimensions - browsing, novelty/utility seeking, and bargain hunting- , in the paratelic state scenario participants with hedonic motivational trait displayed significantly more hedonic shopping behavior intentions than participants with a functional motivational trait (resp. F = 9.701, p = .003; F = 4.979, p = .03; F = 5.757, p = .02); and in the telic state scenario, there was no significant difference in behavior intentions between participants with hedonic or functional motivation trait. Each time, the interaction effect between motivational state and motivational trait was significant (resp. F = 4.859, p = .03; F = 3.314, p = .07; F = 2.98, p = .08). Concerning the fourth dimension, social interaction, shopping behavior intentions of participants with hedonic and with functional motivational traits were significantly different in the paratelic state scenario (F = 29.898, p <.000) as well as in the telic state scenario (F = 9.559, p = .003). However, the interaction effect showed that this behavioral difference was significantly stronger in the paratelic scenario. All these results support our research hypothesis. Discussion and Implications Our study provides consistent support for our hypotheses saying that there is an interaction effect between shopping motivational states and shopping motivational traits. The generalization of the results is strengthened by the study of four different shopping traits: social interaction, novelty/utility seeking, bargain hunting and browsing. As we proposed, when shopping in a goal-oriented state (telic state), behaviors of hedonic and functional shoppers do not differ significantly. Conversely, when shopping for a recreational reason (paratelic state), hedonic and functional shoppers behave significantly different. These results could explain why some previous studies concluded that shopping motivational traits had no impact on shopping behavior: they did not take into consideration the interaction between motivational trait and motivational state. Moreover, our study shows that marketing surveys performed by store managers to draw the personal profile of their customers must be crossed with contextual motivations in order to accurately forecast shopper behavior. Future Developments Our results can be explained by the self-control process, which pushes hedonic-trait shoppers to behave in a rather functional way in utilitarian situations. However, to be certain that this is the very process that occurs, we plan to add self-control perception scales to our existing measures. This is obviously the next step of this research.

Disentangle contextual and permanent individual motivations:an application to shopping behavior

Past studies resulted in conflicting definitions of consumer motivation. Motivations are seen either as the consumer? s characteristics that shape her general behavior (motivational trait), or as contextual variables representing the reason why the individual is behaving specific to today?s context (motivational state). The objective of this research is to understand the impact of each on consumer behavior. Applied to shopping motivations, our study shows a strong interaction between motivational trait and state: motivational traits influence behavior only when associated with a recreational motivational state. In a functional motivational state, individuals prevent their personal characteristics from being fully expressed.

How does bureaucracy impact individual creativity? A cross-level investigation of team contextual influences on goal orientation-creativity relationships

Offering important counterpoint to work identifying team influences stimulating creative expression of individual differences in goal orientation, we develop cross-level theory establishing that team bureaucratic practices (centralization and formalization) constrain creative expression. Speaking to the tension between bureaucracy and creativity, findings indicate that this influence is not only negative and that effects of centralization and formalization differ. Surveying 330 employees in 95 teams at the Taiwan Customs Bureau, we found that learning and "performance avoid" goal orientations had, respectively, stronger positive and weaker negative relationships with creativity under low centralization. A "performance- prove" orientation was positively related to creativity under low formalization. © Academy of Management Journal.

Leader-member exchange and contextual performance:the mediating influence of organization-based self-esteem

This study examined the mediating influence of organization-based self-esteem (OBSE) on the relationship between leader-member exchange (LMX) and contextual performance. Respondents were Indian employees and their immediate supervisors. Results of structural equation modeling (SEM) that compared the fit of a fully mediated model to a partially mediated model revealed support for the hypothesized fully mediated model. Specifically, the SEM results showed the relationship between LMX and the contextual performance facets of interpersonal facilitation and job dedication to be indirect, through OBSE. Support for the hypothesized mediating influence of OBSE highlights the multiple motivational underpinnings of contextual performance

Abusive supervision and contextual performance:The mediating role of emotional exhaustion and the moderating role of work unit structure

This study examined the processes linking abusive supervision to employee contextual performance by focusing on the mediating influence of emotional exhaustion and the moderating influence of work unit structure. Data were obtained from 285 subordinate-supervisor dyads from three manufacturing companies in north-eastern China. The results revealed that: (i) emotional exhaustion mediated the relationships between abusive supervision and the contextual performance dimensions of interpersonal facilitation and job dedication; and (ii) work unit structure moderated these relationships such that the relationships were stronger in mechanistic than in organic work unit structures. © 2008 Blackwell Publishing Ltd.

Contextual semantics for sentiment analysis of Twitter

Sentiment analysis on Twitter has attracted much attention recently due to its wide applications in both, commercial and public sectors. In this paper we present SentiCircles, a lexicon-based approach for sentiment analysis on Twitter. Different from typical lexicon-based approaches, which offer a fixed and static prior sentiment polarities of words regardless of their context, SentiCircles takes into account the co-occurrence patterns of words in different contexts in tweets to capture their semantics and update their pre-assigned strength and polarity in sentiment lexicons accordingly. Our approach allows for the detection of sentiment at both entity-level and tweet-level. We evaluate our proposed approach on three Twitter datasets using three different sentiment lexicons to derive word prior sentiments. Results show that our approach significantly outperforms the baselines in accuracy and F-measure for entity-level subjectivity (neutral vs. polar) and polarity (positive vs. negative) detections. For tweet-level sentiment detection, our approach performs better than the state-of-the-art SentiStrength by 4-5% in accuracy in two datasets, but falls marginally behind by 1% in F-measure in the third dataset.

Adapting sentiment lexicons using contextual semantics for sentiment analysis of Twitter

Sentiment lexicons for sentiment analysis offer a simple, yet effective way to obtain the prior sentiment information of opinionated words in texts. However, words' sentiment orientations and strengths often change throughout various contexts in which the words appear. In this paper, we propose a lexicon adaptation approach that uses the contextual semantics of words to capture their contexts in tweet messages and update their prior sentiment orientations and/or strengths accordingly. We evaluate our approach on one state-of-the-art sentiment lexicon using three different Twitter datasets. Results show that the sentiment lexicons adapted by our approach outperform the original lexicon in accuracy and F-measure in two datasets, but give similar accuracy and slightly lower F-measure in one dataset.