Text Analytics of Social Media: Sentiment Analysis, Event Detection and Summarization

In the last decade, large numbers of social media services have emerged and been widely used in people's daily life as important information sharing and acquisition tools. With a substantial amount of user-contributed text data on social media, it becomes a necessity to develop methods and tools for text analysis for this emerging data, in order to better utilize it to deliver meaningful information to users. Previous work on text analytics in last several decades is mainly focused on traditional types of text like emails, news and academic literatures, and several critical issues to text data on social media have not been well explored: 1) how to detect sentiment from text on social media; 2) how to make use of social media's real-time nature; 3) how to address information overload for flexible information needs. In this dissertation, we focus on these three problems. First, to detect sentiment of text on social media, we propose a non-negative matrix tri-factorization (tri-NMF) based dual active supervision method to minimize human labeling efforts for the new type of data. Second, to make use of social media's real-time nature, we propose approaches to detect events from text streams on social media. Third, to address information overload for flexible information needs, we propose two summarization framework, dominating set based summarization framework and learning-to-rank based summarization framework. The dominating set based summarization framework can be applied for different types of summarization problems, while the learning-to-rank based summarization framework helps utilize the existing training data to guild the new summarization tasks. In addition, we integrate these techneques in an application study of event summarization for sports games as an example of how to better utilize social media data.

Radionuclides, Nd isotopes and biogenic Opal in Atlanic Ocean sediments

Reconstructing past modes of ocean circulation is an essential task in paleoclimatology and paleoceanography. To this end, we combine two sedimentary proxies, Nd isotopes (epsilon-Nd) and the 231Pa/230Th ratio, both of which are not directly involved in the global carbon cycle, but allow the reconstruction of water mass provenance and provide information about the past strength of overturning circulation, respectively. In this study, combined 231Pa/230Th and epsilon-Nd down-core profiles from six Atlantic Ocean sediment cores are presented. The data set is complemented by the two available combined data sets from the literature. From this we derive a comprehensive picture of spatial and temporal patterns and the dynamic changes of the Atlantic Meridional Overturning Circulation over the past ~25 ka. Our results provide evidence for a consistent pattern of glacial/stadial advances of Southern Sourced Water along with a northward circulation mode for all cores in the deeper (>3000 m) Atlantic. Results from shallower core sites support an active overturning cell of shoaled Northern Sourced Water during the LGM and the subsequent deglaciation. Furthermore, we report evidence for a short-lived period of intensified AMOC in the early Holocene.

Derivation of base-line geochemistry, petrography, and isotopic data for the host rocks to the Lucky Strike deposit and comparison with data from other alteration zones, Buchans Mining Camp, Newfoundland

The Buchans ore bodies of central Newfoundland represent some of the highest grade VMS deposits ever mined. These Kuroko-type deposits are also known for the well developed and preserved nature of the mechanically transported deposits. The deposits are hosted in Cambro-Ordovician, dominantly calc-alkaline, bimodal volcanic and epiclastic sequences of the Notre Dame Subzone, Newfoundland Appalachians. Stratigraphic relationships in this zone are complicated by extensively developed, brittledominated Silurian thrust faulting. Hydrothermal alteration of host rocks is a common feature of nearly all VMS deposits, and the recognition of these zones has been a key exploration tool. Alteration of host rocks has long been described to be spatially associated with the Buchans ore bodies, most notably with the larger in-situ deposits. This report represents a base-line study in which a complete documentation of the geochemical variance, in terms of both primary (igneous) and alteration effects, is presented from altered volcanic rocks in the vicinity of the Lucky Strike deposit (LSZ), the largest in-situ deposit in the Buchans camp. Packages of altered rocks also occur away from the immediate mining areas and constitute new targets for exploration. These zones, identified mostly by recent and previous drilling, represent untested targets and include the Powerhouse (PHZ), Woodmans Brook (WBZ) and Airport (APZ) alteration zones, as well as the Middle Branch alteration zone (MBZ), which represents a more distal alteration facies related to Buchans ore-formation. Data from each of these zones were compared to those from the LSZ in order to evaluate their relative propectivity. Derived litho geochemical data served two functions: (i) to define primary (igneous) trends and (ii) secondary alteration trends. Primary trends were established using immobile, or conservative, elements (i. e., HFSE, REE, Th, Ti0₂, Al₂0₃, P₂0₅). From these, altered volcanic rocks were interpreted in terms of composition (e.g., basalt - rhyodacite) and magmatic affinity (e.g., calc-alkaline vs. tholeiitic). The information suggests that bimodality is a common feature of all zones, with most rocks plotting as either basalt/andesite or dacite (or rhyodacite); andesitic senso stricto compositions are rare. Magmatic affinities are more varied and complex, but indicate that all units are arc volcanic sequences. Rocks from the LSZ/MBZ represent a transitional to calc-alkalic sequence, however, a slight shift in key geochemical discriminants occurs between the foot-wall to the hanging-wall. Specifically, mafic and felsic lavas of the foot-wall are of transitional (or mildly calc-alkaline) affinity whereas the hanging-wall rocks are relatively more strongly calc-alkaline as indicated by enriched LREE/HREE and higher ZrN, NbN and other ratios in the latter. The geochemical variations also serve as a means to separate the units (at least the felsic rocks) into hanging-wall and foot-wall sequences, therefore providing a valuable exploration tool. Volcanic rocks from the WBZ/PHZ (and probably the APZ) are more typical of tholeiitic to transitional suites, yielding flatter mantlenormalized REE patterns and lower ZrN ratios. Thus, the relationships between the immediate mining area (represented by LSZ/MBZ) and the Buchans East (PHZ/WBZ) and the APZ are uncertain. Host rocks for all zones consist of mafic to felsic volcanic rocks, though the proportion of pyroclastic and epiclastic rocks, is greatest at the LSZ. Phenocryst assemblages and textures are common in all zones, with minor exceptions, and are not useful for discrimination purposes. Felsic rocks from all zones are dominated by sericiteclay+/- silica alteration, whereas mafic rocks are dominated by chlorite- quartz- sericite alteration. Pyrite is ubiquitous in all moderately altered rocks and minor associated base metal sulphides occur locally. The exception is at Lucky Strike, where stockwork quartzveining contains abundant base-metal mineralization and barite. Rocks completely comprised of chlorite (chloritite) also occur in the LSZ foot-wall. In addition, K-feldspar alteration occurs in felsic volcanic rocks at the MBZ associated with Zn-Pb-Ba and, notably, without chlorite. This zone represents a peripheral, but proximal, zone of alteration induced by lower temperature hydrothermal fluids, presumably with little influence from seawater. Alteration geochemistry was interpreted from raw data as well as from mass balanced (recalculated) data derived from immobile element pairs. The data from the LSZ/MBZ indicate a range in the degree of alteration from only minor to severe modification of precursor compositions. Ba tends to show a strong positive correlation with K₂0, although most Ba occurs as barite. With respect to mass changes, Al₂0₃, Ti0₂ and P₂0₅ were shown to be immobile. Nearly all rocks display mass loss of Na₂O, CaO, and Sr reflecting feldspar destruction. These trends are usually mirrored by K₂0-Rb and MgO addition, indicating sericitic and chloritic alteration, respectively. More substantial gains ofK₂0 often occur in rocks with K-feldspar alteration, whereas a few samples also displayed excessive MgO enrichment and represent chloritites. Fe₂0₃ indicates both chlorite and sulphide formation. Si0₂ addition is almost always the case for the altered mafic rocks as silica often infills amygdules and replaces the finer tuffaceous material. The felsic rocks display more variability in Si0₂. Silicic, sericitic and chloritic alteration trends were observed from the other zones, but not K-feldspar, chloritite, or barite. Microprobe analysis of chlorites, sericites and carbonates indicate: (i) sericites from all zones are defined as muscovite and are not phengitic; (ii) at the LSZ, chlorites ranged from Fe-Mg chlorites (pycnochlorite) to Mg-rich chlorite (penninite), with the latter occurring in the stockwork zone and more proximal alteration facies; (iii) chlorites from the WBZ were typical of those from the more distal alteration facies of the LSZ, plotting as ripidolite to pycnochlorite; (iv) conversely, chlorite from the PHZ plot with Mg-Al-rich compositions (chlinochlore to penninite); and (v) carbonate species from each zone are also varied, with calcite occurring in each zone, in addition to dolomite and ankerite in the PHZ and WBZ, respectively. Lead isotope ratios for galena separates from the different various zones, when combined with data from older studies, tend to cluster into four distinctive fields. Overall, the data plot on a broad mixing line and indicate evolution in a relatively low-μ environment. Data from sulphide stringers in altered MBZ rocks, as well as from clastic sulphides (Sandfill prospect), plot in the Buchans ore field, as do the data for galena from altered rocks in the APZ. Samples from the Buchans East area are even more primitive than the Buchans ores, with lead from the PHZ plotting with the Connel Option prospect and data from the WBZ matching that of the Skidder prospect. A sample from a newly discovered debris flow-type sulphide occurrence (Middle Branch East) yields lead isotope ratios that are slightly more radiogenic than Buchans and plot with the Mary March alteration zone. Data within each cluster are interpreted to represent derivation from individual hydrothermal systems in which metals were derived from a common source.

Mining the Online Social Network Data: Influence, Summarization, and Organization

Online Social Network (OSN) services provided by Internet companies bring people together to chat, share the information, and enjoy the information. Meanwhile, huge amounts of data are generated by those services (they can be regarded as the social media ) every day, every hour, even every minute, and every second. Currently, researchers are interested in analyzing the OSN data, extracting interesting patterns from it, and applying those patterns to real-world applications. However, due to the large-scale property of the OSN data, it is difficult to effectively analyze it. This dissertation focuses on applying data mining and information retrieval techniques to mine two key components in the social media data — users and user-generated contents. Specifically, it aims at addressing three problems related to the social media users and contents: (1) how does one organize the users and the contents? (2) how does one summarize the textual contents so that users do not have to go over every post to capture the general idea? (3) how does one identify the influential users in the social media to benefit other applications, e.g., Marketing Campaign? The contribution of this dissertation is briefly summarized as follows. (1) It provides a comprehensive and versatile data mining framework to analyze the users and user-generated contents from the social media. (2) It designs a hierarchical co-clustering algorithm to organize the users and contents. (3) It proposes multi-document summarization methods to extract core information from the social network contents. (4) It introduces three important dimensions of social influence, and a dynamic influence model for identifying influential users.

Towards Next Generation Vertical Search Engines

As the Web evolves unexpectedly fast, information grows explosively. Useful resources become more and more difficult to find because of their dynamic and unstructured characteristics. A vertical search engine is designed and implemented towards a specific domain. Instead of processing the giant volume of miscellaneous information distributed in the Web, a vertical search engine targets at identifying relevant information in specific domains or topics and eventually provides users with up-to-date information, highly focused insights and actionable knowledge representation. As the mobile device gets more popular, the nature of the search is changing. So, acquiring information on a mobile device poses unique requirements on traditional search engines, which will potentially change every feature they used to have. To summarize, users are strongly expecting search engines that can satisfy their individual information needs, adapt their current situation, and present highly personalized search results. In my research, the next generation vertical search engine means to utilize and enrich existing domain information to close the loop of vertical search engine's system that mutually facilitate knowledge discovering, actionable information extraction, and user interests modeling and recommendation. I investigate three problems in which domain taxonomy plays an important role, including taxonomy generation using a vertical search engine, actionable information extraction based on domain taxonomy, and the use of ensemble taxonomy to catch user's interests. As the fundamental theory, ultra-metric, dendrogram, and hierarchical clustering are intensively discussed. Methods on taxonomy generation using my research on hierarchical clustering are developed. The related vertical search engine techniques are practically used in Disaster Management Domain. Especially, three disaster information management systems are developed and represented as real use cases of my research work.

Transformative Learning Theory and Its Relevance to Managing Group Dynamics in a Competitive Work Environment

In any environment, group dynamics would exist. How we deal with it in a competitive work environment defines who we are using transformative learning. This paper provides useful information from a number of theorists who share perspectives on the complex nature of groups.

Annotated record of the detailed examination of Mn deposits from R.R.S. "Discovery" Cruise 11 stations

During Discovery Cruise 11, April-May 1966, eleven hauls were made on the crest and on the southern facing slope of Palmer Ridge in the Peake Deep area in order to fill out the information gained last year. Limestones were collected ranging in age from lowest Eocene through to Upper Tertiary, and several hauls successfully sampled the basement beneath these, producing weathered basalts, metamorphosed basalts and dolerites. In Peake Deep on the north slope of Palmer Ridge hard Eocene sediments were core sampled near the base of the slope but no cores could be got near the top.

Systematic review of Late Jurassic sauropods from the Museu Geológico collections (Lisboa, Portugal)

The Museu Geológico collections house some of the first sauropod references of the Lusitanian Basin Upper Jurassic record, including the Lourinhasaurus alenquerensis and Lusotitan atalaiensis lectotypes, previously considered as new species of the Apatosaurus and Brachiosaurus genera, respectively. Several fragmentary specimens have been classical referred to those taxa, but the most part of these systematic attributions are not supported herein, excluding a caudal vertebra from Maceira (MG 8804) considered as cf. Lusotitan atalaiensis. From the material housed in the Museu Geológico were identified basal eusauropods (indeterminate eusauropods and turiasaurs) and neosauropods (indeterminate neosauropods, diplodods and camarasaurids and basal titanosauriforms). Middle caudal vertebrae with lateral fossae, ventral hollow border by pronounced ventrolateral crests and quadrangular cross-section suggest for the presence of diplodocine diplodocids in north area of the Lusitanian Basin Central Sector during the Late Jurassic. A humerus collected from Praia dos Frades (MG 4976) is attributed to cf. Duriatitan humerocristatus suggesting the presence of shared sauropod forms between the Portugal and United Kingdom during the Late Jurassic. Duriatitan is an indeterminate member of Eusauropoda and the discovery of new material in both territories is necessary to confirm this systematic approach. The studied material is in according with the previous recorded paleobiodiversity for the sauropod clade during the Portuguese Late Jurassic, which includes basal eusauropods (including turiasaurs), diplodocids and macronarians (including camarasaurids and basal titanosauriforms).

Examples of “land stewarship” in Brazil. The “Projecto Sempre Viva” (Mucugê-Bahia)

In recent years the concept of "Land Stewardship" has gained a great importance. In short, it means that local entities and individuals can protect enclave of high ecological and cultural value. This vision has been effective in some places in the world with success. For example, the “Projeto Sempre Viva”, created in the town of Mucugê, a place located in one of Brazil´s most renowned Natural Protected Areas: the Chapada Diamantina (State of Bahia). We had looked over the available information about this project on the Internet, as well as a personal visit that was made to the site to know it and to have the possibility to talk to their managers. On this basis, it has been reached to the conclusion that this project, born to protect a Sempre Viva´s endemic species in danger of extinction, has turned into an important site for tourism and environmental education, completed with the preservation of the cultural identity of this region which is linked to diamond mining.

Discovery and settlement of Alaska coaster

Tsar Peter the Great ruled Russia between 1689 and 1725. Its domains, stretching from the Baltic Sea in the west to the Pacific Ocean in the east. From north to south, its empire stretching from the Arctic Ocean to the borders with China and India. Tsar Peter I tried to extend the geographical knowledge of his government and the rest of the world. He was also interested in the expansion of trade in Russia and in the control of trade routes. Feodor Luzhin and Ivan Yeverinov explored the eastern border of the Russian Empire, the trip between 1719 and 1721 and reported to the Tsar. They had crossed the peninsula of Kamchatka, from west to east and had traveled from the west coast of Kamchatka to the Kuril Islands. The information collected led to the first map of Kamchatka and the Kuril Islands. Tsar Peter ordered Bering surf the Russian Pacific coast, build ships and sail the seas north along the coast to regions of America. The second expedition found equal to those of the previous explorers difficulties. Two ships were eventually thrown away in Okhotsk in 1740. The explorers spent the winter of 1740-1741 stockpiling supplies and then navigate to Petropavlovsk. The two ships sailed eastward and did together until June 20, then separated by fog. After searching Chirikov and his boat for several days, Bering ordered the San Pedro continue to the northeast. There the Russian sailors first sighted Alaska. According to the log, "At 12:30 (pm July 17) in sight of snow-capped mountains and between them a high volcano." This finding came the day of St. Elijah and so named the mountain.

Classifying Written Texts Through Rhythmic Features

Rhythm analysis of written texts focuses on literary analysis and it mainly considers poetry. In this paper we investigate the relevance of rhythmic features for categorizing texts in prosaic form pertaining to different genres. Our contribution is threefold. First, we define a set of rhythmic features for written texts. Second, we extract these features from three corpora, of speeches, essays, and newspaper articles. Third, we perform feature selection by means of statistical analyses, and determine a subset of features which efficiently discriminates between the three genres. We find that using as little as eight rhythmic features, documents can be adequately assigned to a given genre with an accuracy of around 80 %, significantly higher than the 33 % baseline which results from random assignment.

Machine learning classification of surgical pathology reports and chunk recognition for information extraction noise reduction

Background and aims: Machine learning techniques for the text mining of cancer-related clinical documents have not been sufficiently explored. Here some techniques are presented for the pre-processing of free-text breast cancer pathology reports, with the aim of facilitating the extraction of information relevant to cancer staging.

Materials and methods: The first technique was implemented using the freely available software RapidMiner to classify the reports according to their general layout: ‘semi-structured’ and ‘unstructured’. The second technique was developed using the open source language engineering framework GATE and aimed at the prediction of chunks of the report text containing information pertaining to the cancer morphology, the tumour size, its hormone receptor status and the number of positive nodes. The classifiers were trained and tested respectively on sets of 635 and 163 manually classified or annotated reports, from the Northern Ireland Cancer Registry.

Results: The best result of 99.4% accuracy – which included only one semi-structured report predicted as unstructured – was produced by the layout classifier with the k nearest algorithm, using the binary term occurrence word vector type with stopword filter and pruning. For chunk recognition, the best results were found using the PAUM algorithm with the same parameters for all cases, except for the prediction of chunks containing cancer morphology. For semi-structured reports the performance ranged from 0.97 to 0.94 and from 0.92 to 0.83 in precision and recall, while for unstructured reports performance ranged from 0.91 to 0.64 and from 0.68 to 0.41 in precision and recall. Poor results were found when the classifier was trained on semi-structured reports but tested on unstructured.

Conclusions: These results show that it is possible and beneficial to predict the layout of reports and that the accuracy of prediction of which segments of a report may contain certain information is sensitive to the report layout and the type of information sought.

Data Mining for Network Intrusion Detection : A comparison of data mining algorithms and an analysis of relevant features for detecting cyber-attacks

Data mining can be defined as the extraction of implicit, previously un-known, and potentially useful information from data. Numerous re-searchers have been developing security technology and exploring new methods to detect cyber-attacks with the DARPA 1998 dataset for Intrusion Detection and the modified versions of this dataset KDDCup99 and NSL-KDD, but until now no one have examined the performance of the Top 10 data mining algorithms selected by experts in data mining. The compared classification learning algorithms in this thesis are: C4.5, CART, k-NN and Naïve Bayes. The performance of these algorithms are compared with accuracy, error rate and average cost on modified versions of NSL-KDD train and test dataset where the instances are classified into normal and four cyber-attack categories: DoS, Probing, R2L and U2R. Additionally the most important features to detect cyber-attacks in all categories and in each category are evaluated with Weka’s Attribute Evaluator and ranked according to Information Gain. The results show that the classification algorithm with best performance on the dataset is the k-NN algorithm. The most important features to detect cyber-attacks are basic features such as the number of seconds of a network connection, the protocol used for the connection, the network service used, normal or error status of the connection and the number of data bytes sent. The most important features to detect DoS, Probing and R2L attacks are basic features and the least important features are content features. Unlike U2R attacks, where the content features are the most important features to detect attacks.

Collaborative Filtering with Data Classification : A Combined Approach to Hotel Recommendation Systems

Recommendation systems aim to help users make decisions more efficiently. The most widely used method in recommendation systems is collaborative filtering, of which, a critical step is to analyze a user's preferences and make recommendations of products or services based on similarity analysis with other users' ratings. However, collaborative filtering is less usable for recommendation facing the "cold start" problem, i.e. few comments being given to products or services. To tackle this problem, we propose an improved method that combines collaborative filtering and data classification. We use hotel recommendation data to test the proposed method. The accuracy of the recommendation is determined by the rankings. Evaluations regarding the accuracies of Top-3 and Top-10 recommendation lists using the 10-fold cross-validation method and ROC curves are conducted. The results show that the Top-3 hotel recommendation list proposed by the combined method has the superiority of the recommendation performance than the Top-10 list under the cold start condition in most of the times.

Bento Box Discovery

Poster presentation at the University of Maryland Libraries Research & Innovative Practice Forum on June 8, 2016. The poster proposes that the UMD Libraries should evaluate adoption of Bento Box Discovery for improved user search experience.